jpp.bib

@techreport{pedroso1996niche-treport,
  author = {Jo{\~a}o P. Pedroso},
  title = {{Niche Search:} {A}n {O}bject-{O}riented
                  implementation in the {C++} programming language},
  institution = {CORE, UCL},
  year = 1996,
  abstract = {A (rather dated) description of the classes that
                  intervene in Niche Search.}
}
@inproceedings{pedroso1996ppsn,
  author = {Jo{\~a}o Pedro Pedroso},
  title = {Niche Search: An Evolutionary Algorithm for Global
                  Optimisation},
  booktitle = {PPSN},
  year = 1996,
  pages = {430-440},
  ee = {http://dx.doi.org/10.1007/3-540-61723-X_1007},
  crossref = {zzz:DBLP:conf/ppsn/1996},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  pdf = {PDF/niche-ppsn.pdf},
  abstract = {In this paper we describe niche search, a
                  genetic-based optimisation approach which is
                  characterised by an evolutionary search on two
                  layers: the individual layer (which is comparable to
                  search described in other genetic algorithms), and
                  the niche layer.  Neither of these searches is
                  directed: both individuals and niches evolve based
                  on the selection of the fittest.  The numerical
                  results obtained by niche search are quite
                  promising, as our implementation has successfully
                  handled all the tests carried out.  The
                  computational performance is considerably better
                  than that of other algorithms of the same family
                  analysed in the literature.  }
}
@inproceedings{pedroso1996seal,
  author = {Jo{\~a}o P. Pedroso},
  title = {Numerical solution of {N}ash and {S}tackelberg
                  equilibria: an evolutionary approach},
  booktitle = {Proceedings of the First Asia Conference on
                  Simulated Evolution and Learning},
  xcrossref = {should be in procSEAL96},
  year = 1996,
  organization = {First Asia Conference on Simulated Evolution and
                  Learning (SEAL'96)},
  address = {Taejon, Korea},
  jppnote = {>>> should be Lecture notes in Artificial
                  Intelligence},
  jppbooktitle = {>>> Lecture notes in Artificial Intelligence},
  jpppublisher = {>>> Springer-Verlag},
  pages = {151-160},
  pdf = {PDF/nash-es.pdf},
  abstract = { In this paper we describe evolutionary heuristics
                  for numerically solving systems of several,
                  interdependent optimisation problems.  They can be
                  used for the solution of some games with
                  simultaneous moves of the players (Nash equilibria),
                  asynchronous moves (Stackelberg equilibria), or a
                  mix of these situations.  The application is
                  possible in cases where the presence of
                  non-convexities, integral variables, or other
                  factors restrain the use of traditional methods,
                  based on derivatives.  The solution of instances of
                  well known economic equilibrium problems with these
                  algorithms is supplied.  The results obtained for
                  these simple cases show potential applications of
                  the strategies, and provide limited convergence
                  evidence.}
}
@techreport{pedroso1997mnpdp,
  author = {Jo{\~a}o P. Pedroso},
  title = {Niche Search: an Application to the {M}anhattan
                  Newspaper Problem},
  institution = {Center for Operations Research and Econometrics},
  year = 1997,
  type = {Discussion Paper},
  number = 9765,
  address = {Universit{\'e} Catholique de Louvain,
                  Louvain-la-Neuve, Belgium},
  abstract = { In this paper we describe a hybrid strategy for
                  solving combinatorial optimisation problems,
                  obtained by coupling a local search method to an
                  evolutionary algorithm, and we provide an
                  application to the Manhattan newspaper problem.  The
                  local search method has been devised specifically
                  for this class of problems.  It is based on a
                  composite neighbourhood, which is searched
                  iteratively up to the point where no further
                  improvements can be made.  The evolutionary
                  structure is the niche search, an algorithm based on
                  the evolution of several independent niches.  Niches
                  whose individuals' fitness is good remain, and the
                  others tend to be replaced.  The separation of the
                  population into niches allows for a good compromise
                  between intensive search (inside each niche) and
                  diversification (through the separation between the
                  niches).  },
  pdf = {PDF/manhattan-dp.pdf}
}
@inproceedings{pedroso1997noltalib,
  author = {Jo{\~a}o P. Pedroso},
  title = {Implementation of a library for modelling in
                  economics: design guidelines},
  booktitle = {Proceedings of the 1997 International Symposium on
                  Nonlinear Theory and its Applications},
  crossref = {procNOLTA97},
  pages = {297-300},
  year = 1997,
  abstract = { In this paper we propose some design guidelines for
                  the implementation of a library for computer aided
                  modelling and analysis in economics.  We base our
                  approach in object-oriented programming.  We also
                  introduce a prototype implementation, where a set of
                  algorithms and data structures appropriated for
                  economic modelling is supplied.  },
  pdf = {PDF/econ-lib.pdf}
}
@inproceedings{pedroso1997noltapar,
  author = {Jo{\~a}o P. Pedroso},
  title = {Control of search parameters in evolutionary
                  algorithms},
  booktitle = {Proceedings of the 1997 International Symposium on
                  Nonlinear Theory and its Applications},
  crossref = {procNOLTA97},
  pages = {1265-1268},
  year = 1997,
  abstract = { In this paper we present a strategy for
                  automatically adapting the control parameters of an
                  evolutionary algorithm.  Its main features consist
                  on its simplicity, and on providing total
                  independence of the type of problem being solved.  },
  pdf = {PDF/control-pars.pdf}
}
@techreport{pedroso1998bsis,
  author = {Jo{\~a}o P. Pedroso},
  title = {An evolutionary solver for linear integer
                  programming},
  institution = {Riken Brain Science Institute},
  year = 1998,
  type = {BSIS Technical Report},
  number = {98-7},
  address = {Wako-shi, Saitama, Japan},
  abstract = {In this paper we introduce an evolutionary algorithm
                  for the solution of linear integer programs.  The
                  strategy is based on the separation of the set of
                  variables into the integer subset and the continuous
                  subset; the integer variables are fixed by the
                  evolutionary system, and the continuous ones are
                  determined in function of them, by a linear program
                  solver.  If they correspond to a feasible solution,
                  their evaluation is determined directly by the
                  objective function.  If the variables correspond to
                  an infeasible solution, the evaluation is measured
                  by the minimal sum of constraint violations.
                  Solutions closer to feasibility are preferred,
                  without regard to the objective function.  We report
                  results obtained for some standard benchmark
                  instances, and compare them with those obtained by
                  branch-and-bound.  The performance of the
                  evolutionary algorithm is promising.  Good feasible
                  solutions were generally obtained, and in some of
                  the difficult benchmark tests the algorithm
                  outperformed branch-and-bound.  },
  pdf = {PDF/mip-ga-tr9807.pdf}
}
@inproceedings{pedroso1998icec,
  author = {Jo{\~a}o P. Pedroso},
  title = {Niche Search: an Application in Vehicle Routing},
  booktitle = {IEEE International Conference on Evolutionary
                  Computation},
  crossref = {procICEC98},
  year = 1998,
  pages = {177-182},
  abstract = {In this paper we describe a hybrid strategy for
                  solving combinatorial optimisation problems,
                  obtained by coupling a local search method to an
                  evolutionary algorithm, and we provide an
                  application to a particular variant of the vehicle
                  routing problem.  The local search method has been
                  devised specifically for this class of problems.  It
                  is based on a composite neighbourhood, which is
                  searched iteratively up to the point where no
                  further improvements can be made.  The evolutionary
                  structure is the niche search, an algorithm based on
                  the evolution of several independent niches.  Niches
                  whose individuals' fitness is good remain, and the
                  others tend to be replaced.  The separation of the
                  population into niches allows for a good compromise
                  between intensive search (inside each niche) and
                  diversification (through the separation between the
                  niches).  We also describe how we integrate specific
                  problem knowledge into an evolutionary structure, in
                  order to achieve a high performance optimisation
                  algorithm.  All the steps that we consider necessary
                  are described in detail: finding an appropriate
                  representation, determining what is a relevant
                  neighbourhood, setting up a local search method and
                  finally integrating the local search into an
                  evolutionary algorithm.  },
  pdf = {PDF/manhattan-icec.pdf}
}
@techreport{pedroso1999bsis,
  author = {Jo{\~a}o P. Pedroso and Noboru Murata},
  title = {Support vector machines for linear programming:
                  motivation and formulation},
  institution = {Riken Brain Science Institute},
  year = 1999,
  type = {BSIS Technical Report},
  number = {99-2},
  address = {Wako-shi, Saitama, Japan},
  ps = {lin-svm.ps.gz},
  abstract = { We introduce two formulations for training support
                  vector machines, based on considering the $L_1$ and
                  $L_\infty$ norms instead of the currently used $L_2$
                  norm, and maximising the margin between the
                  separating hyperplane and each data sets using $L_1$
                  and $L_\infty$ distances.  We exploit the
                  geometrical properties of these different norms, and
                  propose what kind of results should be expected for
                  them.  Formulations in mathematical programming for
                  linear problems corresponding to $L_1$ and
                  $L_\infty$ norms are also provided, for both the
                  separable and non separable cases.  We report
                  results obtained for some standard benchmark
                  problems, which confirmed that the performance of
                  all the formulations is similar.  As expected, the
                  CPU time required for machines solvable with linear
                  programming is much shorter.  }
}
@techreport{pedroso1999cio,
  author = {Jo{\~a}o P. Pedroso},
  title = {An evolutionary solver for pure integer linear
                  programming},
  institution = {Centro de Investiga{\c{c}}{\~a}o Operacional da
                  Universidade de Lisboa},
  year = 1999,
  type = {Working Paper},
  number = {5/99},
  address = {Centro de Investiga{\c{c}}{\~a}o Operacional,
                  Faculdade de Ci\^encias da Universidade de Lisboa,
                  1749-016 Lisboa, Portugal},
  ps = {pip-ga.ps.gz},
  abstract = {In this paper we introduce an evolutionary algorithm
                  for the solution of pure integer linear programs.
                  All the variables of the problem are fixed by the
                  evolutionary system.  If they correspond to a
                  feasible solution, their evaluation is determined
                  directly by the objective function.  If the
                  variables correspond to an infeasible solution, the
                  evaluation is measured by the sum of
                  infeasibilities, which can be determined by simple
                  linear algebra manipulations.  The algorithm
                  proposed does not require the solution of continuous
                  linear programs.  We report results obtained for
                  some standard benchmark problems, and compare them
                  with those obtained by branch-and-bound.  The
                  performance of the evolutionary algorithm is
                  promising.  Good feasible solutions were generally
                  obtained, and in some of the difficult benchmark
                  tests it outperformed branch-and-bound.  }
}
@inproceedings{pedroso2000ijcnn,
  author = {Jo{\~a}o P. Pedroso and Noboru Murata},
  title = {Optimisation on support vector machines},
  booktitle = {IEEE-INNS-ENNS International Joint Conference on
                  Neural Networks},
  pages = {399-404},
  year = 2000,
  editor = {Shun-Ichi Amari and C. Lee Giles and Marco Gori and
                  Vincenzo Piuri},
  volume = {VI},
  pdf = {PDF/svm-ijcnn-2000.pdf},
  abstract = {In this paper we deal with the optimisation problem
                  involved in determining the maximal margin
                  separation hyperplane in support vector machines.
                  We consider three different formulations, based on
                  $L_2$ norm distance (the standard case), $L_1$ norm,
                  and $L_\infty$ norm.  We consider separation in the
                  original space of the data (i.e., there are no
                  kernel transformations).  For any of these cases, we
                  focus on the following problem: having the optimal
                  solution for a given training data set, one is given
                  a new training example.  The purpose is to use the
                  information about the solution of the problem
                  without the additional example in order to speed up
                  the new optimisation problem.  We also consider the
                  case of reoptimisation after removing an example
                  from the data set.  We report results obtained for
                  some standard benchmark problems.  }
}
@techreport{pedroso2001cio,
  author = {Jo{\~a}o P. Pedroso},
  title = {Metaheuristics for combinatorial optimisation},
  institution = {Centro de Investiga{\c{c}}{\~a}o Operacional da
                  Universidade de Lisboa},
  year = 2001,
  type = {Working Paper},
  number = {9/01},
  address = {Centro de Investiga{\c{c}}{\~a}o Operacional,
                  Faculdade de Ci\^encias da Universidade de Lisboa,
                  1749-016 Lisboa, Portugal},
  abstract = {The use of metaheuristics for solving combinatorial
                  optimisation has now a long history, and there are
                  virtually no well-known, hard optimisation problems
                  for which a metaheuristic has not been applied.
                  Often, metaheuristics obtain the best known
                  solutions for hard, large-size real problems, for
                  which exact methods are too time consuming to be
                  applied in in practice.  There are many successful
                  applications reported in the literature; still, to
                  the best of our knowledge there are no mathematical
                  programming languages with an interface to solvers
                  based on metaheuristics.  Mathematical programming
                  being the traditional, powerful way of modelling
                  combinatorial problems, we believe that it would be
                  an important achievement to have a solver based on
                  metaheuristics callable from mathematical
                  programming systems.  In this paper we will focus on
                  the different aspects to take into account when
                  designing a metaheuristic which can be applied to
                  any combinatorial optimisation problem modelled in
                  mathematical programming.  },
  pdf = {PDF/ip-mh.pdf}
}
@inproceedings{pedroso2001dlsp,
  author = {Ana S. Pereira and Filipe Carvalho and Jo{\~a}o
                  P. Pedroso and Miguel Constantino},
  title = {Iterated Local Search and Tabu Search for a Discrete
                  Lot Sizing and Scheduling Problem},
  booktitle = {Proceedings of the Fourth Metaheuristics
                  International Conference},
  pages = {697-701},
  year = 2001,
  editor = {Jorge P. Sousa and Mauricio G. C. Resende},
  address = {Porto, Portugal},
  pdf = {PDF/dlsp.pdf},
  abstract = { In this paper we describe iterated local search and
                  tabu search for solving a multi-item, multi-machine
                  discrete lot sizing and scheduling problem with
                  sequence dependent changeover costs.  We present two
                  construction heuristics with a random component; one
                  of them is purely random and another is based on the
                  linear programming relaxation of the mixed integer
                  programming model. They are used to generate initial
                  solutions for iterated local search and tabu search.
                  We also propose two ways of exploring the
                  neighbourhoods, one based on a random subset of the
                  whole neighbourhood, and another based on exploring
                  the whole neighbourhood.  Construction and
                  improvement methods were combined on iterated local
                  search and tabu search, leading to a total of eight
                  different methods.  We present results of extensive
                  computer experiments for analysing the performance
                  of all methods and their comparison with
                  branch-and-bound, and conclude with some remarks on
                  the different approaches to the problem.  }
}
@inproceedings{pedroso2001neto,
  author = {Teresa Neto and Jo{\~a}o P. Pedroso},
  title = {GRASP for linear integer programming},
  booktitle = {Proceedings of the Fourth Metaheuristics
                  International Conference},
  pages = {377-385},
  year = 2001,
  editor = {Jorge P. Sousa and Mauricio G. C. Resende},
  address = {Porto, Portugal},
  ps = {mip-grasp.ps},
  abstract = { In this paper we introduce a GRASP for the solution
                  of general linear integer problems. The strategy is
                  based on the separation of the set of variables into
                  the integer subset and the continuous subset. The
                  integer variables are fixed by GRASP and replaced in
                  the original linear problem. If the original problem
                  had continuous variables, we have now a pure
                  continuous problem, which can be solved by a linear
                  program solver to determine the objective value
                  corresponding to the fixed variables. If the
                  original problem was a pure integer problem, simple
                  algebraic manipulations can be used to determine the
                  objective value that corresponds to the fixed
                  variables. When we assign values to integer
                  variables that lead to an impossible linear problem,
                  the evaluation of the corrresponding solution is
                  given by the sum of infeasibilities, together with
                  an infeasibility flag.  We report results obtained
                  for some standard benchmark problems, and compare
                  them to those obtained by branch-and-bound.  }
}
@inproceedings{pedroso2001nolta,
  author = {Jo{\~a}o P. Pedroso},
  title = {Metaheuristics using the Simplex Algorithm for
                  Nonlinear Programming},
  booktitle = {Proceedings of the 2001 International Symposium on
                  Nonlinear Theory and its Applications},
  crossref = {procNOLTA2001},
  pages = {315-318},
  year = 2001,
  abstract = {In this paper we present a metaheuristic for
                  non-linear programming, based on the Nelder and Mead
                  simplex algorithm.  The algorithm proposed is
                  suitable for both unconstrained and constrained
                  optimisation.  We explore several possibilities for
                  escaping local optima.},
  pdf = {PDF/nolta-2001.pdf}
}
@article{pedroso2001prl,
  author = {Jo{\~a}o P. Pedroso and Noboru Murata},
  title = {Support vector machines with different norms:
                  motivation, formulations, and results},
  journal = {Pattern Recognition Letters},
  year = 2001,
  volume = 22,
  pages = {1263-1272},
  abstract = { We introduce two formulations for training support
                  vector machines, based on considering the $L_1$ and
                  $L_\infty$ norms instead of the currently used $L_2$
                  norm, and maximising the margin between the
                  separating hyperplane and each data sets using $L_1$
                  and $L_\infty$ distances.  We exploit the
                  geometrical properties of these different norms, and
                  propose what kind of results should be expected for
                  them.  Formulations in mathematical programming for
                  linear problems corresponding to $L_1$ and
                  $L_\infty$ norms are also provided, for both the
                  separable and non separable cases.  We report
                  results obtained for some standard benchmark
                  problems, which confirmed that the performance of
                  all the formulations is similar.  As expected, the
                  CPU time required for machines solvable with linear
                  programming is much shorter.  },
  jpppdf = {PDF/svm-prl.pdf}
}
@article{pedroso2002itors,
  author = {Jo{\~a}o P. Pedroso},
  title = {An evolutionary solver for pure integer linear
                  programming},
  journal = {International Transactions in Operational Research},
  year = 2002,
  volume = 9,
  number = 3,
  pages = {337-352},
  month = {May},
  abstract = { In this paper we introduce an evolutionary
                  algorithm for the solution of pure integer linear
                  programs.  All the variables of the problem are
                  fixed by the evolutionary system.  If they
                  correspond to a feasible solution, their evaluation
                  is determined directly by the objective function.
                  If the variables correspond to an infeasible
                  solution, the evaluation is measured by the sum of
                  infeasibilities, which can be determined by simple
                  linear algebra manipulations.  The algorithm
                  proposed does not require the solution of continuous
                  linear programs.  We report results obtained for
                  some standard benchmark problems, and compare them
                  with those obtained by branch-and-bound.  The
                  performance of the evolutionary algorithm is
                  promising.  Good feasible solutions were generally
                  obtained, and in some of the difficult benchmark
                  tests it outperformed branch-and-bound.  },
  jpppdf = {PDF/pip-ga.pdf}
}
@inproceedings{pedroso2003cePROC,
  author = {Jo{\~a}o P. Pedroso},
  title = {A multi-agent system for automated timetabling with
                  shared resources},
  booktitle = {Proceedings of the 10th ISPE International
                  Conference on Concurrent Engineering},
  year = 2003,
  editor = {Jianzhong Cha and Ricardo Jardim-Gon{\c c}alves and
                  Adolfo Steiger-Gar{\c c}{\~a}o},
  volume = {2 - Advanced design, management and production
                  systems},
  address = {Madeira Island - Portugal},
  publisher = {A.A. Balkema Publishers},
  abstract = { We propose an automated timetabling system for a
                  typical situation in universities, where agents
                  (usually departments or faculties) compete for a set
                  of resources (lecture rooms) on a given number of
                  time slots.  Each agent uses its own algorithm
                  (which might be unknown to the others).  A central
                  system decides whether some agent is granted a
                  resource or not, based on a list of requests and on
                  a certificate, obtained from each agent, asserting
                  that it does not have requests with priority higher
                  that a certain amount.  Priority is measured
                  primarily by the number of attendees and some
                  requirements for particular features on the
                  resources, but other criteria are proposed for ties.
                  We describe a prototype implementation, in use at
                  the Faculty of Sciences, University of Porto.  },
  pdf = {PDF/ce2003.pdf}
}
@inproceedings{pedroso2003dlsp,
  editor = {Jorge P. Sousa and Mauricio G. C. Resende},
  author = {Ana S. Pereira and Filipe Carvalho and Miguel
                  Constantino and Jo{\~a}o P. Pedroso},
  booktitle = {METAHEURISTICS: Computer Decision-Making},
  title = {Iterated Local Search and Tabu Search for a Discrete
                  Lot Sizing and Scheduling Problem},
  chapter = 27,
  publisher = {Kluwer Academic Publishers},
  year = 2003,
  series = {Combinatorial Optimization Book Series},
  pages = {575-600},
  doi = {10.1007/978-1-4757-4137-7_27},
  pdf = {PDF/dlsp.pdf},
  abstract = { In this paper we describe iterated local search and
                  tabu search for solving a multi-item, multi-machine
                  discrete lot sizing and scheduling problem with
                  sequence dependent changeover costs.  We present two
                  construction heuristics with a random component; one
                  of them is purely random and another is based on the
                  linear programming relaxation of the mixed integer
                  programming model. They are used to generate initial
                  solutions for iterated local search and tabu search.
                  We also propose two ways of exploring the
                  neighbourhoods, one based on a random subset of the
                  whole neighbourhood, and another based on exploring
                  the whole neighbourhood.  Construction and
                  improvement methods were combined on iterated local
                  search and tabu search, leading to a total of eight
                  different methods.  We present results of extensive
                  computer experiments for analysing the performance
                  of all methods and their comparison with
                  branch-and-bound, and conclude with some remarks on
                  the different approaches to the problem.  }
}
@inproceedings{pedroso2003neto,
  editor = {Jorge P. Sousa and Mauricio G. C. Resende},
  author = {Teresa Neto and Jo{\~a}o P. Pedroso},
  booktitle = {METAHEURISTICS: Computer Decision-Making},
  title = {GRASP for linear integer programming},
  chapter = 26,
  publisher = {Kluwer Academic Publishers},
  year = 2003,
  series = {Combinatorial Optimization Book Series},
  pages = {545-574},
  abstract = { In this paper we introduce a GRASP for the solution
                  of general linear integer problems. The strategy is
                  based on the separation of the set of variables into
                  the integer subset and the continuous subset. The
                  integer variables are fixed by GRASP and replaced in
                  the original linear problem. If the original problem
                  had continuous variables, it becomes a pure
                  continuous problem, which can be solved by a linear
                  program solver to determine the objective value
                  corresponding to the fixed variables. If the
                  original problem was a pure integer problem, simple
                  algebraic manipulations can be used to determine the
                  objective value that corresponds to the fixed
                  variables. When we assign values to integer
                  variables that lead to an impossible linear problem,
                  the evaluation of the corresponding solution is
                  given by the sum of infeasibilities, together with
                  an infeasibility flag.  We report results obtained
                  for some standard benchmark problems, and compare
                  them to those obtained by branch-and-bound and to
                  those obtained by an evolutionary solver.  },
  doi = {10.1007/978-1-4757-4137-7_26},
  pdf = {PDF/mip-grasp.pdf}
}
@techreport{pedroso2004h4TR,
  author = {Rog{\'e}rio Reis and Nelma Moreira and Jo{\~a}o
                  Pedro Pedroso},
  title = {Educated brute-force to get $h(4)$},
  institution = {LIACC, Universidade do Porto},
  year = 2004,
  number = {DCC-2004-04},
  abstract = {In one of his numerous conferences, Frank Harary,
                  talked about one of his many games, that, as usual,
                  had a very difficult problem associated to it. In
                  this case, a family of games for two players in
                  which the selected number of columns in the game has
                  a vital importance. He has proved that for 2 and 3
                  columns the longest match has 9 and 24 moves
                  respectively, that is to say that h_2=9 and
                  h_3=24. At the same time it was announced that he
                  knew a solution of length 67 for the problem with 4
                  columns, but he didn't know if it was the
                  maximum. We present here a program that proves that
                  h_4=67. Although it uses but a brute-force approach,
                  its soundness seems good fun to prove.},
  pdf = {PDF/dcc-2004-04.pdf}
}
@inproceedings{pedroso2004ickeds,
  author = {Jo{\~a}o P. Pedroso and Nelma Moreira and
                  Rog{\'e}rio Reis},
  title = {A web-based system for multi-agent interactive
                  timetabling},
  booktitle = {{ICKEDS}'04: International Conference on Knowledge
                  Engineering and Decision Support},
  year = 2004,
  address = {Porto, Portugal},
  month = {July},
  abstract = { We propose a web-based timetabling system for a
                  typical situation in universities, where agents
                  (usually departments or faculties) compete for a set
                  of resources (lecture rooms) on a given number of
                  time slots.  Each agent (typically a person, on the
                  behalf of a department) proposes the placement (room
                  and time) for events.  A dispatching system decides
                  which event should be scheduled next, based on a
                  pre-established set of rules, and asks its placement
                  to the corresponding department.  The system also
                  suggests the placement of an event to each agent,
                  thus allowing a completely automated timetable
                  construction.  We describe a prototype implemented
                  at the Faculty of Sciences, University of Porto.  },
  pdf = {PDF/ickeds2004.pdf}
}
@inproceedings{pedroso2004iss,
  author = {Jo{\~a}o P. Pedroso},
  title = {Metaheuristics for industrial scheduling},
  booktitle = {Proceedings of the International Symposium in
                  Scheduling},
  editor = {Shigeru Masuyama},
  year = 2004,
  address = {Shizuoka, Japan},
  month = {September},
  abstract = { We will analyse the problem of scheduling on batch
                  industries.  A production order for an end product
                  implies the sequential execution of a set of
                  operations; for each operation, there is a set of
                  machines, possibly with different characteristics,
                  able to process it.  After processing an operation,
                  the machines have to be cleaned; the cleaning time
                  is sequence-dependent.  The most usual objective is
                  minimising the makespan for all the orders in hand.
                  In this work we present the fundamental notions
                  concerning the use of metaheuristics for tackling
                  this problem, focusing on construction strategies
                  and neighbourhood structures for local search.  },
  pdf = {PDF/SchedSympShizuoka.pdf},
  anote = {Invited seminar}
}
@techreport{pedroso2004mipenumTR,
  author = {Jo{\~a}o P. Pedroso},
  title = {Hybrid Enumeration Strategies for Mixed Integer
                  Programming},
  institution = {LIACC, Universidade do Porto},
  year = 2004,
  number = {DCC-2004-08},
  pdf = {PDF/mip-enum-WP.pdf},
  abstract = { In this paper we present several algorithms which
                  combine a partial enumeration with metaheuristics
                  for the solution of general mixed-integer
                  programming problems.  The enumeration is based on
                  the primal values assignable to the integer
                  variables of the problem. We develop some algorithms
                  for this integration, and test them using a set of
                  well-known benchmark problems.  }
}
@inproceedings{pedroso2004miptsKLUWER,
  editor = {Cesar Rego},
  author = {Jo{\~a}o P. Pedroso},
  booktitle = {Metaheuristic Optimization via Memory and Evolution:
                  Tabu Search and Scatter Search},
  title = {Tabu Search for Mixed Integer Programming},
  chapter = 11,
  series = {Operations Research/Computer Science Interfaces
                  Series},
  publisher = {Springer},
  year = 2005,
  abstract = { This paper introduces tabu search for the solution
                  of general linear integer problems. Search is done
                  on integer variables; if there are continuous
                  variables, their corresponding value is determined
                  through the solution of a linear program, which is
                  also used to evaluate the integer solution. The
                  complete tabu search procedure includes an
                  intensification and diversification procedure, whose
                  effects are analysed on a set of benchmark problems.
                  },
  pdf = {PDF/mip-ts.pdf}
}
@inproceedings{pedroso2005hm,
  author = {Jo{\~a}o Pedro Pedroso and Mikio Kubo},
  title = {Hybrid Tabu Search for Lot Sizing Problems},
  booktitle = {Hybrid Metaheuristics},
  year = 2005,
  pages = {66-77},
  ee = {http://dx.doi.org/10.1007/11546245_7},
  crossref = {zzz:DBLP:conf/hm/2005},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  abstract = { This paper presents a hybrid tabu search strategy
                  for lot sizing problems.  This strategy allows the
                  exploitation of the quality of the well-known
                  relax-and-fix heuristic, inside a tabu search
                  framework which enforces diversity.  The
                  computational results show an advantage of this
                  strategy when compared to a version of the
                  relax-and-fix heuristic and to time constrained
                  branch-and-bound.  },
  pdf = {PDF/hybrid-ts.pdf}
}
@inproceedings{pedroso2006icdmrodriguesA,
  author = {Pedro Rodrigues and Jo{\~a}o Gama and Jo{\~a}o Pedro
                  Pedroso},
  title = {{ODAC}: Hierarchical Clustering of Time Series Data
                  Streams},
  booktitle = {Proceedings of the Sixth SIAM International
                  Conference on Data Mining},
  year = 2006,
  editor = {Joydeep Ghosh, Diane Lambert, David Skillicorn and
                  Jaideep Srivastava},
  pages = {499-503},
  month = {April},
  address = {Bethesda, Maryland, USA},
  note = {ISBN 0-89871-611-X},
  organization = {SIAM},
  abstract = { This paper presents a time series whole clustering
                  system that incrementally constructs a tree-like
                  hierarchy of clusters, using a top-down strategy.
                  The Online Divisive-Agglomerative Clustering
                  ({ODAC}) system uses a correlation-based
                  dissimilarity measure between time series over a
                  data stream and possesses an agglomerative phase to
                  enhance a dynamic behavior capable of concept drift
                  detection. Main features include splitting and
                  agglomerative criteria based on the diameters of
                  existing clusters and supported by a significance
                  level. At each new example, only the leaves are
                  updated, reducing computation of unneeded
                  dissimilarities and speeding up the process every
                  time the structure grows. Experimental results on
                  artificial and real data suggest competitive
                  performance on clustering time series and show that
                  the system is equivalent to a batch divi- sive
                  clustering on stationary time series, being also
                  capable of dealing with concept drift. With this
                  work, we assure the possibility and importance of
                  hierarchical incremental time series whole
                  clustering in the data stream paradigm, presenting a
                  valuable and usable option.  },
  doi = {10.1137/1.9781611972764.48},
  pdf = {PDF/ODAC.pdf}
}
@techreport{pedroso2007earfmip-DCC,
  author = {Jo{\~a}o P. Pedroso},
  title = {An evolutionary solver for mixed integer
                  programming},
  institution = {DCC, FC, Universidade do Porto},
  year = 2007,
  number = {DCC-2007-09},
  abstract = { In this paper we introduce an evolutionary
                  algorithm for the solution of mixed integer
                  programs.  The strategy is based on the separation
                  of the set of variables into the integer subset and
                  the continuous subset.  The main idea is that if the
                  integer variables are fixed by the evolutionary
                  system, the continuous ones can be determined in
                  function of them by a linear program, which
                  simultaneously provides an evaluation of those
                  variables.  We extend this idea to the case were
                  some of the integer variables are fixed by the
                  evolutionary system and the remaining ones, as well
                  as the continuous ones, are determined in function
                  of them.  Branch-and-bound and a specialised version
                  of the relax-and-fixed heuristic are used to solve
                  the mixed-integer subproblems.  When a particular
                  assignment of the integer variables set by the
                  evolutionary system leads to a feasible solution,
                  its evaluation is determined directly by the
                  objective function.  If the variables correspond to
                  an infeasible solution, the evaluation is measured
                  by the number of variables that could not be fixed,
                  due to infeasibility in the subproblem; solutions
                  with more variables fixed are preferred.  We report
                  results obtained for some standard benchmark
                  instances, and compare them with those obtained by
                  time limited branch-and-bound.  For a set of
                  difficult instances, the evolutionary algorithm
                  could almost always improve the solution obtained by
                  branch-and-bound on the same amount of CPU time.  },
  pdf = {PDF/mip-ga-rf-DCC.pdf}
}
@inproceedings{pedroso2007nlpsimplexLNCS,
  author = {Jo{\~a}o Pedro Pedroso},
  title = {Simple Metaheuristics Using the Simplex Algorithm
                  for Non-linear Programming},
  booktitle = {SLS},
  year = 2007,
  pages = {217-221},
  ee = {http://dx.doi.org/10.1007/978-3-540-74446-7_21},
  crossref = {zzz:DBLP:conf/sls/2007},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  abstract = { In this paper we present an extension of the Nelder
                  and Mead simplex algorithm for non-linear
                  programming, which makes it suitable for both
                  unconstrained and constrained optimisation.  We then
                  explore several extensions of the method for
                  escaping local optima, and which make it a simple,
                  yet powerful tool for optimisation of nonlinear
                  functions with many local optima.  A strategy which
                  proved to be extremely robust was random start local
                  search, with a correct, though unusual, setup.
                  Actually, for some of the benchmarks, this simple
                  metaheuristic remained as the most effective one.
                  The idea is to use a very large simplex at the
                  begin; the initial movements of this simplex are
                  very large, and therefore act as a kind of filter,
                  which naturally drives the search into good areas.
                  We propose two more mechanisms for escaping local
                  optima, which, still being very simple to implement,
                  provide better results for some difficult problems.
                  },
  pdf = {PDF/nlp-simplex-lncs.pdf}
}
@article{pedroso2008clustering,
  author = {Pedro Pereira Rodrigues and Jo{\~a}o Gama and
                  Jo{\~a}o P. Pedroso},
  title = {Hierarchical Clustering of Time Series Data Streams},
  journal = {{IEEE} Transactions on Knowledge and Data
                  Engineering},
  year = 2008,
  volume = 20,
  number = 5,
  pages = {615-627},
  url = {http://dx.doi.org/10.1109/TKDE.2007.190727},
  month = {May},
  abstract = {This paper presents and analyzes an incremental
                  system for clustering streaming time series. The
                  Online Divisive-Agglomerative Clustering ({ODAC})
                  system continuously maintains a tree-like hierarchy
                  of clusters that evolves with data.  {ODAC} uses a
                  top-down strategy. The splitting criterion is a
                  correlation-based dissimilarity measure among time
                  series, splitting each node by the farthest pair of
                  streams, which defines the diameter of the
                  cluster. In stationary environments expanding the
                  structure leads to a decrease in the diameters of
                  the clusters. The system uses a merge operator,
                  which agglomerates two sibling clusters, in order to
                  react to changes in the correlation structure
                  between time series. The split and merge operators
                  are triggered in response to changes in the
                  diameters of existing clusters. The system is
                  designed to process thousands of data streams that
                  flow at high-rate. The main features of the system
                  include update time and memory consumption that do
                  not depend on the number of examples in the
                  stream. Moreover, the time and memory required to
                  process an example decreases whenever the cluster
                  structure expands. Experimental results on
                  artificial and real data assess the processing
                  qualities of the system, suggesting competitive
                  performance on clustering streaming time series,
                  exploring also its ability to deal with concept
                  drift.  },
  jpppdf = {PDF/RGP08.pdf}
}
@incollection{pedroso2008mco,
  author = {Rui Jorge Rei and Mikio Kubo and Jo{\~a}o Pedro
                  Pedroso},
  title = {Simulation-Based Optimization for Steel Stacking},
  booktitle = {MCO},
  year = 2008,
  pages = {254-263},
  ee = {http://dx.doi.org/10.1007/978-3-540-87477-5_28},
  crossref = {zzz:DBLP:conf/mco/2008},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  abstract = { In many sectors of industry, manufacturers possess
                  warehouses where finished goods are stored, awaiting
                  to fulfill a client order.  We present a situation
                  where these items are characterized by release and
                  due dates, i.e. warehouse arrival for storage and
                  client delivery, respectively.  The warehouse has a
                  number of positions available, where items can be
                  placed on top of each other, forming stacks.  For
                  item manipulation, there is a single a stacking
                  crane, able to carry one item at a time.  When in a
                  given stack an item at the top is due at a date
                  later than some item below it, it must be relocated
                  to another stack, so that the item below can be
                  delivered.  In this problem the objective is to
                  minimize the number of movements made by the crane.
                  },
  pdf = {PDF/stacking_rei-kubo-pedroso.pdf}
}
@inproceedings{pedroso2010cie,
  author = {Jo{\~a}o P. Pedroso and Yves Smeers},
  title = {Equilibria on a Game with Discrete Variables},
  booktitle = {Programs, Proofs, Processes},
  year = 2010,
  organization = {Computability in Europe 2010},
  editor = {Fernando Ferreira and H{\'e}lia Guerra and Elvira
                  Mayordomo and Jo{\~a}o Rasga},
  address = {Azores, Portugal},
  pages = {326-335},
  pdf = {PDF/nash-co.pdf},
  abstract = {Equilibrium in Economics has been seldom addressed
                  in a situation where some variables are discrete.
                  This work introduces a problem related to lot-sizing
                  with several players, and analyses some strategies
                  which are likely to be found in real world games.
                  An illustration with a simple example is presented,
                  with concerns about the difficulty of the problem
                  and computation possibilities.}
}
@inproceedings{pedroso2010nma,
  author = {Jo{\~a}o Pedro Pedroso},
  title = {Metaheuristics for the Asymmetric Hamiltonian Path
                  Problem},
  booktitle = {NMA},
  year = 2010,
  pages = {272-279},
  ee = {http://dx.doi.org/10.1007/978-3-642-18466-6_32},
  crossref = {zzz:DBLP:conf/nma/2010},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  pdf = {PDF/nma-atsp.pdf},
  abstract = { One of the most important applications of the
                  Asymmetric Hamiltonian Path Problem is in
                  scheduling.  In this paper we describe a variant of
                  this problem, and develop both a mathematical
                  programming formulation and simple metaheuristics
                  for solving it.  The formulation is based on a
                  transformation of the input data, in such a way that
                  a standard mathematical programming model for the
                  Asymmetric Travelling Salesman Problem can be used
                  on this slightly different problem.  Two standard
                  metaheuristics for the asymmetric travelling
                  salesman are proposed and analysed on this variant:
                  repeated random construction followed by local
                  search with the 3-Exchange neighbourhood, and
                  iterated local search based on the same
                  neighbourhood and on a 4-Exchange perturbation.  The
                  computational results obtained show the interest and
                  the complementary merits of using a mixed-integer
                  programming solver and an approximative method for
                  the solution of this problem.  }
}
@article{pedroso2010npp,
  author = {Jo{\~a}o P. Pedroso and Mikio Kubo},
  title = {Heuristics and Exact Methods for Number
                  Partitioning},
  journal = {European Journal of Operational Research},
  year = 2010,
  volume = 202,
  pages = {73-81},
  url = {http://dx.doi.org/10.1016/j.ejor.2009.04.027},
  doi = {10.1016/j.ejor.2009.04.027},
  abstract = { Number partitioning is a classical NP-hard
                  combinatorial optimization problem, whose solution
                  is challenging for both exact and approximative
                  methods.  This work presents a new algorithm for
                  number partitioning, based on ideas drawn from
                  branch-and-bound, breadth first search, and beam
                  search.  A new set of benchmark instances for this
                  problem is also proposed.  The behavior of the new
                  method on this and other test beds is analyzed and
                  compared to other well known heuristics and exact
                  algorithms.  },
  pdf = {PDF/EJOR_NPP_PedrosoKubo_2010.pdf}
}
@inproceedings{pedroso2011lncs,
  author = {V\'{\i}tor Rodrigues and Jo{\~a}o Pedro Pedroso and
                  M{\'a}rio Florido and Sim{\~a}o Melo de Sousa},
  title = {Certifying Execution Time},
  booktitle = {FOPARA},
  year = 2011,
  pages = {108-125},
  ee = {http://dx.doi.org/10.1007/978-3-642-32495-6_7},
  crossref = {zzz:DBLP:conf/fopara/2011},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
@article{pedroso2012itor,
  author = {Rei, Rui Jorge and Pedroso, Jo{\~a}o Pedro},
  title = {Heuristic search for the stacking problem},
  journal = {International Transactions in Operational Research},
  volume = 19,
  number = 3,
  issn = {1475-3995},
  note = {\url{http://dx.doi.org/10.1111/j.1475-3995.2011.00831.x}},
  pages = {379--395},
  keywords = {Stacking Problem, optimization, simulation,
                  heuristics},
  year = 2012,
  abstract = {This paper presents the Stacking Problem, a hard
                  combinatorial optimization problem concerning
                  handling and storage of items in a warehouse, where
                  they are handled by a crane and organized into
                  stacks. We define the problem, study its complexity
                  class, and present a mathematical programming model
                  to solve it. In order to tackle medium- or
                  large-scale instances, we propose a simulation-based
                  algorithm using semi-greedy construction
                  heuristics. This simple approach allows for multiple
                  constructions, finding solutions within reasonable
                  time even for large instances. Three semi-greedy
                  heuristics are proposed and compared in an extensive
                  computational experiment, where we study the
                  relation between the number of constructions and the
                  best solution obtained using each heuristic.},
  pdfremoved = {PDF/stacking-itor-preview.pdf}
}
@inproceedings{pedroso2012lncs,
  author = {Rui Jorge Rei and Jo{\~a}o Pedro Pedroso and
                  Hideitsu Hino and Noboru Murata},
  title = {A Tree Search Approach to Sparse Coding},
  booktitle = {LION},
  year = 2012,
  pages = {472-477},
  ee = {http://dx.doi.org/10.1007/978-3-642-34413-8_47},
  crossref = {zzz:DBLP:conf/lion/2012},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  abstract = {Sparse coding is an important optimization problem
                  with numerous applications. In this paper, we
                  describe the problem and the commonly used pursuit
                  methods, and propose a best-first tree search
                  algorithm employing multiple queues for unexplored
                  tree nodes. We assess the effectiveness of our
                  method in an extensive computational experiment,
                  showing its superiority over other methods even for
                  modest computational time.},
  pdf = {PDF/sparsecoding_lion6.pdf}
}
@techreport{pedroso2013DCCa,
  author = {Filipe Brand{\~a}o and Jo{\~a}o P. Pedroso},
  title = {Bin Packing and Related Problems: General Arc-flow
                  Formulation with Graph Compression},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2013,
  number = {DCC-2013-08},
  pdf = {PDF/DCC-2013-08.pdf},
  abstract = {We present an exact method, based on an arc-flow
                  formulation with side constraints, for solving bin
                  packing and cutting stock problems --- including
                  multi-constraint variants --- by simply representing
                  all the patterns in a very compact graph. Our method
                  includes a graph compression algorithm that usually
                  reduces the size of the underlying graph
                  substantially without weakening the model. As
                  opposed to our method, which provides strong models,
                  conventional models are usually highly symmetric and
                  provide very weak lower bounds.  Our formulation is
                  equivalent to Gilmore and Gomory's, thus providing a
                  very strong linear relaxation. However, instead of
                  using column-generation in an iterative process, the
                  method constructs a graph, where paths from the
                  source to the target node represent every valid
                  packing pattern.  The same method, without any
                  problem-specific parameterization, was used to solve
                  a large variety of instances from several different
                  cutting and packing problems. In this paper, we deal
                  with vector packing, graph coloring, bin packing,
                  cutting stock, cardinality constrained bin packing,
                  cutting stock with cutting knife limitation, cutting
                  stock with binary patterns, bin packing with
                  conflicts, and cutting stock with binary patterns
                  and forbidden pairs. We report computational results
                  obtained with many benchmark test data sets, all of
                  them showing a large advantage of this formulation
                  with respect to the traditional ones.}
}
@techreport{pedroso2013DCCb,
  author = {Filipe Brand{\~a}o and Jo{\~a}o P. Pedroso},
  title = {Cutting Stock with Binary Patterns: Arc-flow
                  Formulation with Graph Compression},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2013,
  number = {DCC-2013-09},
  pdf = {PDF/DCC-2013-09.pdf},
  abstract = {The cutting stock problem with binary patterns (0-1
                  CSP) is a variant of CSP that usually appears as a
                  relaxation of 2D and 3D packing problems. We present
                  an exact method, based on an arc-flow formulation
                  with side constraints, for solving 0-1 CSP by simply
                  representing all the patterns in a very compact
                  graph.  Gilmore-Gomory's column generation approach
                  is usually used to compute strong lower bounds for
                  0-1 CSP. We report a computational comparison
                  between the arc-flow approach and the
                  Gilmore-Gomory's approach.}
}
@techreport{pedroso2013DCCc,
  author = {Filipe Brand{\~a}o and Jo{\~a}o P. Pedroso},
  title = {Fast Pattern-based Algorithms for Cutting Stock},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2013,
  number = {DCC-2013-10},
  pdf = {PDF/DCC-2013-10.pdf},
  abstract = {The conventional assignment-based first/best fit
                  decreasing algorithms (FFD/BFD) are not polynomial
                  in the cutting stock input size in its most common
                  format. Therefore, even for small instances with
                  large demands, it is difficult to compute FFD/BFD
                  solutions. We present pattern-based methods that
                  overcome the main problems of conventional
                  heuristics in cutting stock problems by representing
                  the solution in a much more compact format. Using
                  our pattern-based heuristics, FFD/BFD solutions for
                  extremely large cutting stock instances, with
                  billions of items, can be found in a very short
                  amount of time.  }
}
@techreport{pedroso2013DCCd,
  author = {Filipe Brand{\~a}o and Jo{\~a}o P. Pedroso},
  title = {Multiple-choice Vector Bin Packing: Arc-flow
                  Formulation with Graph Compression},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2013,
  number = {DCC-2013-13},
  pdf = {PDF/DCC-2013-13.pdf},
  abstract = {The vector bin packing problem (VBP) is a
                  generalization of bin packing with multiple
                  constraints. In this problem we are required to pack
                  items, represented by p-dimensional vectors, into as
                  few bins as possible. The multiple-choice vector bin
                  packing (MVBP) is a variant of the VBP in which bins
                  have several types and items have several
                  incarnations. We present an exact method, based on
                  an arc-flow formulation with graph compression, for
                  solving MVBP by simply representing all the patterns
                  in a very compact graph. As a proof of concept we
                  report computational results on a variable-sized bin
                  packing data set.  }
}
@article{pedroso2013aor,
  author = {Rui Jorge Rei and Jo{\~a}o Pedro Pedroso},
  title = {Tree search for the stacking problem},
  journal = {Annals of Operations Research},
  volume = 203,
  number = 1,
  year = 2013,
  pages = {371-388},
  ee = {http://dx.doi.org/10.1007/s10479-012-1186-2},
  abstract = {The stacking problem is a hard combinatorial
                  optimization problem with high practical interest
                  in, for example, steel storage or container port
                  operations. In this problem, a set of items is
                  stored in a warehouse for a period of time, and a
                  crane is used to place them in a limited number of
                  stacks. Since the entrance and exit of items occurs
                  in an arbitrary order, items may have to be
                  relocated in order to reach and deliver other items
                  below them. The objective of the problem is to find
                  a feasible sequence of movements that delivers all
                  items, while minimizing the total number of
                  movements.  We propose two heuristic methods to
                  solve the problem, and study the scalability of an
                  exact approach. The two heuristic approaches are a
                  multiple simulation algorithm using semi-greedy
                  construction heuristics, and a stochastic best-first
                  tree search algorithm. The two methods are compared
                  in a set of challenging instances, revealing a
                  superior performance of the tree search approach in
                  most cases.  },
  pdf = {PDF/ANOR_Stacking_ReiPedroso2013.pdf}
}
@article{pedroso2013ejco,
  author = {Brand{\~a}o, Filipe and Pedroso, Jo{\~a}o Pedro},
  year = 2013,
  issn = {2192-4406},
  journal = {EURO Journal on Computational Optimization},
  doi = {10.1007/s13675-013-0010-3},
  title = {A complete search method for the relaxed traveling
                  tournament problem},
  url = {http://dx.doi.org/10.1007/s13675-013-0010-3},
  publisher = {Springer-Verlag},
  keywords = {Traveling tournament problem; Branch-and-bound;
                  Metaheuristics; Dynamic programming; 90-08
                  Computational methods; 90-XX Operations research;
                  mathematical programming},
  pages = {1-10},
  language = {English},
  abstract = { The Traveling Tournament Problem (TTP) is a sports
                  scheduling problem that includes two major issues in
                  creating timetables: home/away pattern feasibility
                  and travel distance.  In this problem the schedule
                  must be compact: every team plays in every time
                  slot.  However, there are some sports leagues that
                  have both home/away pattern restrictions and
                  distance limits, but do not require a compact
                  schedule.  In such schedules, one or more teams can
                  have a bye in any time slot.  This leads us to a
                  variant of the problem: the Relaxed Traveling
                  Tournament Problem (RTTP).  We present a complete
                  search method to solve this problem based on
                  branch-and-bound, metaheuristics and dynamic
                  programming.  },
  pdf = {PDF/Brandao_2013_EURO_J_Comput_Optim.pdf}
}
@article{pedroso2013ijepes,
  author = {Ana Viana and J. P. Pedroso},
  title = {A new {MILP}-based approach for unit commitment in
                  power production planning},
  journal = {International Journal of Electrical Power and Energy
                  Systems},
  year = 2013,
  volume = 44,
  pages = {997-1005},
  note = {\url{http://dx.doi.org/10.1016/j.ijepes.2012.08.046}},
  abstract = {This paper presents a complete, quadratic
                  programming formulation of the standard thermal unit
                  commitment problem in power generation planning,
                  together with a novel iterative optimisation
                  algorithm for its solution.  The algorithm, based on
                  a mixed-integer formulation of the problem,
                  considers piecewise linear approximations of the
                  quadratic fuel cost function that are dynamically
                  updated in an iterative way, converging to the
                  optimum; this avoids the requirement of resorting to
                  quadratic programming, making the solution process
                  much quicker.  From extensive computational tests on
                  a broad set of benchmark instances of this problem,
                  the algorithm was found to be flexible and capable
                  of easily incorporating different problem
                  constraints.  Indeed, it is able to tackle ramp
                  constraints, which although very important in
                  practice were rarely considered in previous
                  publications.  Most importantly, optimal solutions
                  were obtained for several well-known benchmark
                  instances, including instances of practical
                  relevance, that are not yet known to have been
                  solved to optimality.  Computational experiments and
                  their results showed that the method proposed is
                  both simple and extremely effective.  },
  pdf = {PDF/IJEPES_UCP_VianaPedroso_2013.pdf}
}
@techreport{pedroso2013kepDCC,
  author = {Jo{\~a}o P. Pedroso},
  title = {Maximizing expectation on vertex-disjoint cycle
                  packing},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2013,
  number = {DCC-2013-05},
  pdf = {PDF/DCC-2013-05_KEP.pdf},
  abstract = {This paper proposes a method for computing the
                  expectation for the length of the maximum set of
                  vertex-disjoint cycles in a digraph where vertices
                  and/or arcs are subject to failure with a known
                  probability.  This method has an immediate practical
                  application: it can be used for the solution of a
                  kidney exchange program in the common situation
                  where the underlying graph is unreliable.  Results
                  for realistic benchmark instances are reported and
                  analyzed.}
}
@article{pedroso2013netoITOR,
  author = {Teresa Neto and Miguel Constantino and Jo{\~a}o
                  P. Pedroso and Isabel Martins},
  title = {A branch-and-bound procedure for forest harvest
                  scheduling problems addressing aspects of habitat
                  availability},
  journal = {International Transactions in Operational Research},
  url = {http://dx.doi.org/10.1111/itor.12003},
  doi = {10.1111/itor.12003},
  volume = 20,
  number = 5,
  pages = {689--709},
  issn = {1475-3995},
  year = 2013,
  keywords = {forestry, branch and bound, integer programming,
                  tree algorithms, scheduling},
  abstract = { In the literature, the most referenced approaches
                  for forest harvesting scheduling problems addressing
                  environmental protection issues have focused mainly
                  on including constraints on clearcut
                  area. Nevertheless, these restrictions may not be
                  sufficient to prevent the loss of habitat
                  availability that endangers the survival of many
                  wild species.  This work presents a tree search
                  procedure for finding good feasible solutions, in
                  reasonable times, to forest harvest scheduling
                  problems with constraints on clearcut area and
                  habitat availability.  We use two measures for
                  habitat availability: the area of all habitats and
                  the connectivity between them.  For solving the
                  problem, we use a tree search procedure: a process
                  inspired in branch-and-bound, specifically designed
                  for this problem.  In each branch, a partial
                  solution leads to two children nodes, corresponding
                  to harvesting or not a given stand in a given
                  period.  Pruning is based on constraint violations
                  or on unreachable objective values. Preliminary
                  computational results are reported.  },
  pdf = {PDF/Neto_et_al-2013-International_Transactions_in_Operational_Research.pdf}
}
@techreport{pedroso2014DCC05,
  author = {Jo{\~a}o P. Pedroso and Mikio Kubo and Ana Viana},
  title = {Unit commitment with valve-point loading effect},
  institution = {DCC, Faculdade de Ci{\^e}ncias, Universidade do
                  Porto},
  year = 2014,
  number = {DCC-2014-05},
  pdf = {PDF/dcc-2014-05.pdf},
  abstract = {Valve-point loading affects the input-output
                  characteristics of generating units, bringing the
                  fuel costs nonlinear and nonsmooth.  This has been
                  considered in the solution of load dispatch
                  problems, but not in the planning phase of unit
                  commitment.  This paper presents a mathematical
                  optimization model for the thermal unit commitment
                  problem considering valve-point loading.  The
                  formulation is based on a careful linearization of
                  the fuel cost function, which is modeled with great
                  detail on power regions being used in the current
                  solution, and roughly on other regions.  A set of
                  benchmark instances for this problem is used for
                  analyzing the method, with recourse to a
                  general-purpose mixed-integer optimization solver.}
}
@article{pedroso2014aims,
  author = {Margarida Carvalho and Jo{\~a}o P. Pedroso and
                  Jo{\~a}o Saraiva},
  title = {Electricity Day-Ahead Markets: Computation of Nash
                  Equilibria},
  journal = {Journal of Industrial and Management Optimization},
  volume = 11,
  number = 3,
  pages = {985--998},
  year = 2014,
  doi = {10.3934/jimo.2015.11.985},
  url = {http://aimsciences.org/journals/displayArticlesnew.jsp?paperID=10449},
  issn = {1547-5816},
  abstract = {In a restructured electricity sector, day-ahead
                  markets can be modeled as a game where some players
                  - the producers - submit their proposals. To analyze
                  the companies' behavior we have used the concept of
                  Nash equilibrium as a solution in these multi-agent
                  interaction problems. In this paper, we present new
                  and crucial adaptations of two well-known
                  mechanisms, the adjustment process and the
                  relaxation algorithm, in order to achieve the goal
                  of computing Nash equilibria. The advantages of
                  these approaches are highlighted and compared with
                  those available in the literature.},
  publisher = {American Institute of Mathematical Sciences},
  pdf = {PDF/nash_elect_2011.pdf}
}
@article{pedroso2014cor,
  title = {Fast pattern-based algorithms for cutting stock},
  journal = {Computers \& Operations Research },
  volume = 48,
  pages = {69--80},
  year = 2014,
  issn = {0305-0548},
  doi = {http://dx.doi.org/10.1016/j.cor.2014.03.003},
  url = {http://www.sciencedirect.com/science/article/pii/S0305054814000525},
  author = {Filipe Brand{\~a}o and Jo{\~a}o Pedro Pedroso},
  abstract = {The conventional assignment-based first/best fit
                  decreasing algorithms (FFD/BFD) are not polynomial
                  in the one-dimensional cutting stock input size in
                  its most common format. Therefore, even for small
                  instances with large demands, it is difficult to
                  compute FFD/BFD solutions. We present pattern-based
                  methods that overcome the main problems of
                  conventional heuristics in cutting stock problems by
                  representing the solution in a much more compact
                  format. Using our pattern-based heuristics, FFD/BFD
                  solutions for extremely large cutting stock
                  instances, with billions of items, can be found in a
                  very short amount of time.},
  keywords = {Cutting stock},
  keywords = {First fit decreasing},
  keywords = {Best fit decreasing },
  pdf = {PDF/COR2014.pdf}
}
@article{pedroso2014ijdats,
  author = {Nicolau Santos and Rui Rebelo and Jo{\~a}o
                  P. Pedroso},
  title = {A Tabu Search for the Flowshop Scheduling Problem
                  with Sequence Dependent Setup Times},
  year = 2014,
  journal = {International Journal of Data Analysis Techniques
                  and Strategies},
  volume = 6,
  number = 3,
  pages = {275--285},
  abstract = {In this work we present a tabu search metaheuristic
                  method for solving the permutation flow shop
                  scheduling problem with sequence dependent setup
                  times and the objective of minimizing total weighted
                  tardiness. The problem is well known for its
                  practical applications and for the difficulty in
                  obtaining good solutions. The tabu search method
                  proposed is based on the insertion neighborhood, and
                  is characterized by the selection and evaluation of
                  a small subset of this neighborhood at each
                  iteration; this has consequences both on
                  diversification and intensification of the
                  search. We also propose a speed-up technique based
                  on book keeping information of the current solution,
                  used for the evaluation of its neighbors.  },
  pdf = {PDF/ts_pfs_ijdats_2012.pdf}
}
@article{pedroso2014ijepes,
  title = {Metaheuristic search based methods for unit
                  commitment },
  journal = {International Journal of Electrical Power and Energy
                  Systems },
  volume = 59,
  number = 0,
  pages = {14 - 22},
  year = 2014,
  issn = {0142-0615},
  doi = {http://dx.doi.org/10.1016/j.ijepes.2014.01.038},
  url = {http://www.sciencedirect.com/science/article/pii/S0142061514000519},
  author = {Dewan Fayzur Rahman and Ana Viana and Jo{\~a}o Pedro
                  Pedroso},
  keywords = {Unit commitment},
  keywords = {Combinatorial optimization},
  keywords = {Matheuristics },
  abstract = {This paper presents two new solution approaches
                  capable of finding optimal solutions for the thermal
                  unit commitment problem in power generation
                  planning. The approaches explore the concept of
                  "matheuristics", a term usually used to refer to an
                  optimization algorithm that hybridizes
                  (meta)heuristics with mixed integer programming
                  solvers, in order to speed up convergence to
                  optimality for large scale instances. Two algorithms
                  are proposed: "local branching", and an
                  hybridization of particle swarm optimization with a
                  mixed integer programming solver.  From extensive
                  computational tests on a broad set of benchmarks,
                  the algorithms were found to be able to solve large
                  instances. Optimal solutions were obtained for
                  several well-known situations with dramatic
                  reductions in CPU time for the larger cases, when
                  compared to previously proposed exact methods.},
  pdf = {PDF/ucp-ijepes-2014.pdf}
}
@incollection{pedroso2014lncsCOA,
  year = 2014,
  isbn = {978-3-319-09128-0},
  booktitle = {Computational Science and Its Applications -- ICCSA
                  2014},
  volume = 8580,
  series = {Lecture Notes in Computer Science},
  editor = {Murgante, Beniamino and Misra, Sanjay and Rocha, Ana
                  Maria A.C. and Torre, Carmelo and Rocha, Jorge
                  Gustavo and Falc{\~a}o, Maria Irene and Taniar,
                  David and Apduhan, Bernady O. and Gervasi, Osvaldo},
  doi = {10.1007/978-3-319-09129-7_3},
  title = {Maximizing Expectation on Vertex-Disjoint Cycle
                  Packing},
  url = {http://dx.doi.org/10.1007/978-3-319-09129-7_3, },
  pdf = {PDF/DCC-2013-05_KEP.pdf},
  publisher = {Springer International Publishing},
  keywords = {Kidney exchange programs; Cycle packing; Expectation
                  optimization; Combinatorial optimization},
  author = {Pedroso, Jo{\~a}o Pedro},
  pages = {32-46},
  language = {English},
  abstract = {This paper proposes a method for computing the
                  expectation for the length of a maximum set of
                  vertex-disjoint cycles in a digraph where vertices
                  and/or arcs are subject to failure with a known
                  probability.  This method has an immediate practical
                  application: it can be used for the solution of a
                  kidney exchange program in the common situation
                  where the underlying graph is unreliable.  Results
                  for realistic benchmark instances are reported and
                  analyzed.}
}
@inproceedings{pedroso2014tron,
  author = {Jo{\~a}o Pedro Pedroso},
  title = {Optimization and Artificial Intelligence for Smart
                  Devices},
  booktitle = {T-Engine Forum},
  year = 2014,
  address = {Tokyo, Japan},
  organization = {IEEE Consumer Electronics Society},
  pdf = {PDF/ia-smart-devices.pdf}
}
@incollection{pedroso2014ucpFayzur,
  year = 2014,
  isbn = {978-3-319-00794-6},
  booktitle = {Operations Research Proceedings 2012},
  series = {Operations Research Proceedings},
  editor = {Helber, Stefan and Breitner, Michael and R{\"o}sch,
                  Daniel and Sch{\"o}n, Cornelia and Graf von der
                  Schulenburg, Johann-Matthias and Sibbertsen, Philipp
                  and Steinbach, Marc and Weber, Stefan and Wolter,
                  Anja},
  doi = {10.1007/978-3-319-00795-3_23},
  title = {A {MILP}-Based Approach for Hydrothermal Scheduling},
  url = {http://dx.doi.org/10.1007/978-3-319-00795-3_23},
  publisher = {Springer International Publishing},
  author = {Rahman, Dewan Fayzur and Viana, Ana and Pedroso,
                  Jo{\~a}o Pedro},
  abstract = {This paper presents new solution approaches capable
                  of finding optimal solutions for the Hydrothermal
                  Scheduling Problem (HSP) in power generation
                  planning. The problem has been proven to be NP-hard
                  and no exact methods have been able to tackle it,
                  for problem sizes of practical relevance. We explore
                  three approaches. The first method is an iterative
                  algorithm that has been successfully used previously
                  to solve the thermal commitment problem. The two
                  other methods are "Local Branching" and a
                  hybridization of "Particle Swarm Optimization" with
                  a general purpose solver. Computational experiments
                  show that the iterative piecewise linear
                  approximation method outperforms more elaborated
                  approaches, indicating that recourse to
                  matheuristics for solving this problem is not
                  necessary.},
  pages = {157-162},
  language = {English},
  pdf = {PDF/MILP-HydSched-2012.pdf}
}
@incollection{pedroso2015mctsASO,
  isbn = {978-3-319-15032-1},
  booktitle = {Applied Simulation and Optimization},
  editor = {Mujica Mota, Miguel and De La Mota, Idalia Flores
                  and Guimarans Serrano, Daniel},
  doi = {10.1007/978-3-319-15033-8_4},
  title = {Tree Search and Simulation},
  url = {http://dx.doi.org/10.1007/978-3-319-15033-8_4},
  publisher = {Springer International Publishing},
  author = {Jo{\~a}o P. Pedroso and Rui Rei},
  pages = {109-131},
  year = 2015,
  abstract = {This chapter presents a methodology for embodying
                  simulation as part of a tree search procedure, as a
                  technique for solving practical problems in
                  combinatorial optimization.  Target problems either
                  are difficult to express as mixed integer
                  optimization models, or have models which provide
                  rather loose bounds; in both cases, traditional,
                  exact methods typically fail.  The idea used is to
                  have tree search instantiating part of the
                  variables, in a systematic way, and for that
                  particular instantiation---a node in the search
                  tree---resort to a simulation for assigning values
                  to the remaining variables; then, use the outcome of
                  the simulation for evaluating that node in the tree.
                  This method has been used with considerable success
                  in game playing, but has received very limited
                  attention as a tool for optimization.  Nevertheless,
                  it has great potential, either as a way for
                  improving known heuristics or as an alternative to
                  metaheuristics.  We depart from repeated, randomized
                  simulation based on problem-specific heuristics for
                  applications in scheduling, logistics, and packing,
                  and show how the systematic search in a tree
                  improves the results that can be obtained.},
  pdf = {PDF/mcts_chapter.pdf}
}
@article{pedroso2015scp,
  title = {Certifying execution time in multicores },
  journal = {Science of Computer Programming },
  volume = 111,
  number = {P3},
  pages = {505--534},
  month = {November},
  year = 2015,
  issn = {0167-6423},
  doi = {10.1016/j.scico.2015.06.006},
  url = {http://dx.doi.org/10.1016/j.scico.2015.06.006},
  author = {V{\'\i}tor Rodrigues and Benny Akesson and M{\'a}rio
                  Florido and Sim{\~a}o Melo de Sousa and Jo{\~a}o
                  Pedro Pedroso and Pedro Vasconcelos},
  keywords = {Abstract interpretation},
  keywords = {Verification},
  keywords = {\{ACC\}},
  keywords = {\{WCET\}},
  keywords = {\{LP\}},
  keywords = {\{LR\} -servers },
  abstract = {Abstract This article presents a semantics-based
                  program verification framework for critical embedded
                  real-time systems using the worst-case execution
                  time (WCET) as the safety parameter. The
                  verification algorithm is designed to run on devices
                  with limited computational resources where efficient
                  resource usage is a requirement. For this purpose,
                  the framework of abstract-carrying code (ACC) is
                  extended with an additional verification mechanism
                  for linear programming (LP) by applying the
                  certifying properties of duality theory to check the
                  optimality of \{WCET\} estimates. Further, the
                  \{WCET\} verification approach preserves feasibility
                  and scalability when applied to multicore
                  architectural models. The certifying \{WCET\}
                  algorithm is targeted to architectural models based
                  on the \{ARM\} instruction set and is presented as a
                  particular instantiation of a compositional
                  data-flow framework supported on the theoretic
                  foundations of denotational semantics and abstract
                  interpretation. The data-flow framework has
                  algebraic properties that provide algorithmic
                  transformations to increase verification efficiency,
                  mainly in terms of verification time. The \{WCET\}
                  analysis/verification on multicore architectures
                  applies the formalism of latency-rate ( \{LR\} )
                  servers, and proves its correcteness in the context
                  of abstract interpretation, in order to ease
                  \{WCET\} estimation of programs sharing resources. },
  pdf = {PDF/certET2015.pdf}
}
@article{pedroso2016EPSR,
  title = {A multiple criteria utility-based approach for unit
                  commitment with wind power and pumped storage hydro
                  },
  journal = {Electric Power Systems Research },
  volume = 131,
  pages = {244 - 254},
  year = 2016,
  issn = {0378-7796},
  doi = {http://dx.doi.org/10.1016/j.epsr.2015.10.024},
  url = {http://www.sciencedirect.com/science/article/pii/S037877961500320X},
  author = {Bruno Vieira and Ana Viana and Manuel Matos and
                  Jo{\~a}o Pedro Pedroso},
  keywords = {Multiple criteria analysis},
  keywords = {Utility theory},
  keywords = {Uncertainty modelling},
  keywords = {Unit commitment},
  keywords = {Wind power },
  abstract = {Abstract The integration of wind power in
                  electricity generation brings new challenges to the
                  unit commitment problem, as a result of the random
                  nature of the wind speed. The scheduling of thermal
                  generation units at the day-ahead stage is usually
                  based on wind power forecasts. Due to technical
                  limitations of thermal units, deviations from those
                  forecasts during intra-day operations may lead to
                  unwanted consequences, such as load shedding and
                  increased operating costs. Wind power forecasting
                  uncertainty has been handled in practice by means of
                  conservative stochastic scenario-based optimization
                  models, or through additional operating reserve
                  settings. However, generation companies may have
                  different attitudes towards the risks associated to
                  wind power variability. In this paper, operating
                  costs and load shedding are modeled by non-linear
                  utility functions aggregated into a single additive
                  utility function of a multi-objective
                  model. Computational experiments have been done to
                  validate the approach: firstly we test our model for
                  the wind–thermal unit commitment problem and, in a
                  second stage, pumped storage hydro units are added,
                  leading to a model with wind–hydro-thermal
                  coordination. Results have shown that the proposed
                  methodology is able to correctly reflect different
                  risk profiles of decision makers for both models. },
  pdf = {PDF/Vieira_MC-UCP-WindHydro_2016.pdf}
}
@article{pedroso2016corBPP,
  title = {Bin packing and related problems: General arc-flow
                  formulation with graph compression },
  journal = {Computers \& Operations Research },
  volume = 69,
  pages = {56 - 67},
  year = 2016,
  issn = {0305-0548},
  doi = {http://dx.doi.org/10.1016/j.cor.2015.11.009},
  url = {http://www.sciencedirect.com/science/article/pii/S0305054815002762},
  author = {Filipe Brand{\~a}o and Jo{\~a}o Pedro Pedroso},
  keywords = {Bin packing},
  keywords = {Cutting stock},
  keywords = {Vector packing},
  keywords = {Arc-flow formulation },
  abstract = {Abstract We present an exact method, based on an
                  arc-flow formulation with side constraints, for
                  solving bin packing and cutting stock
                  problems—including multi-constraint variants—by
                  simply representing all the patterns in a very
                  compact graph. Our method includes a graph
                  compression algorithm that usually reduces the size
                  of the underlying graph substantially without
                  weakening the model. Our formulation is equivalent
                  to Gilmore and Gomory׳s, thus providing a very
                  strong linear relaxation. However, instead of using
                  column-generation in an iterative process, the
                  method constructs a graph, where paths from the
                  source to the target node represent every valid
                  packing pattern. The same method, without any
                  problem-specific parameterization, was used to solve
                  a large variety of instances from several different
                  cutting and packing problems. In this paper, we deal
                  with vector packing, bin packing, cutting stock,
                  cardinality constrained bin packing, cutting stock
                  with cutting knife limitation, bin packing with
                  conflicts, and other problems. We report
                  computational results obtained with many benchmark
                  test datasets, some of them showing a large
                  advantage of this formulation with respect to the
                  traditional ones. },
  pdf = {PDF/BrandaoPedroso_COR_2016.pdf}
}
@article{pedroso2016corKEP,
  title = {Maximising expectation of the number of transplants
                  in kidney exchange programmes },
  journal = {Computers \& Operations Research },
  volume = 73,
  pages = {1 - 11},
  year = 2016,
  issn = {0305-0548},
  doi = {http://dx.doi.org/10.1016/j.cor.2016.03.004},
  url = {http://www.sciencedirect.com/science/article/pii/S0305054816300533},
  author = {Xenia Klimentova and João Pedro Pedroso and Ana
                  Viana},
  keywords = {Kidney exchange programmes},
  keywords = {Cycle packing},
  keywords = {Expectation optimisation },
  abstract = {This paper addresses the problem of maximising the
                  expected number of transplants in kidney exchange
                  programmes. New schemes for matching rearrangement
                  in case of failure are presented, along with a new
                  tree search algorithm used for the computation of
                  optimal expected values. Extensive computational
                  experiments demonstrate the effectiveness of the
                  algorithm and reveal a clear superiority of a newly
                  proposed scheme, subset-recourse, as compared to
                  previously known approaches. },
  pdf = {PDF/kep-kpv-caor-2016.pdf}
}
@article{pedroso2016itorOCC,
  author = {Pedroso, Jo{\~a}o Pedro and Cunha, S{\'\i}lvia and
                  Tavares, Jo{\~a}o Nuno},
  title = {Recursive circle packing problems},
  journal = {International Transactions in Operational Research},
  volume = 23,
  number = {1-2},
  issn = {1475-3995},
  url = {http://dx.doi.org/10.1111/itor.12107},
  doi = {10.1111/itor.12107},
  pages = {355--368},
  keywords = {packing problems, knapsack problems, heuristics,
                  practice of OR, combinatorial optimization, integer
                  programming, loading problems, local search},
  year = 2016,
  pdf = {PDF/ITOR-RCP-2015.pdf}
}
@article{pedroso2016mathprog,
  author = {Carvalho, Margarida and Lodi, Andrea and Pedroso,
                  Jo{\~a}o Pedro and Viana, Ana},
  title = {Nash equilibria in the two-player kidney exchange
                  game},
  journal = {Mathematical Programming},
  year = {2016},
  pages = {1--29},
  issn = {1436-4646},
  doi = {10.1007/s10107-016-1013-7},
  url = {http://dx.doi.org/10.1007/s10107-016-1013-7},
  abstract = {Kidney exchange programs have been set in several
                  countries within national, regional or hospital
                  frameworks, to increase the possibility of kidney
                  patients being transplanted. For the case of
                  hospital programs, it has been claimed that
                  hospitals would benefit if they collaborated with
                  each other, sharing their internal pools and
                  allowing transplants involving patients of different
                  hospitals. This claim led to the study of
                  multi-hospital exchange markets. We propose a novel
                  direction in this setting by modeling the exchange
                  market as an integer programming game. The analysis
                  of the strategic behavior of the entities
                  participating in the kidney exchange game allowed us
                  to prove that the most rational game outcome
                  maximizes the social welfare and that it can be
                  computed in polynomial time.}
}
@article{pedroso2016forest,
  author = {Neto, Teresa and Constantino, Miguel and Martins,
                  Isabel and Pedroso, João Pedro},
  year = {2016},
  title = {Forest harvest scheduling with clearcut and core
                  area constraints},
  journal = {Annals of Operations Research},
  issn = {0254-5330},
  doi = {10.1007/s10479-016-2313-2},
  url = {https://dx.doi.org/10.1007/s10479-016-2313-2},
  month = {9},
  abstract = {Many studies regarding environmental concerns in
                  forest harvest scheduling problems deal with
                  constraints on the maximum clearcut size. However,
                  these constraints tend to disperse harvests across
                  the forest and thus to generate a more fragmented
                  landscape. When a forest is fragmented, the amount
                  of edge increases at the expense of the core
                  area. Highly fragmented forests can neither provide
                  the food, cover, nor the reproduction needs of
                  core-dependent species. This study presents a
                  branch-and-bound procedure designed to find good
                  feasible solutions, in a reasonable time, for forest
                  harvest scheduling problems with constraints on
                  maximum clearcut size and minimum core habitat
                  area. The core area is measured by applying the
                  concept of subregions. In each branch of the
                  branch-and-bound tree, a partial solution leads to
                  two children nodes, corresponding to the cases of
                  harvesting or not a given stand in a given
                  period. Pruning is based on constraint violations or
                  unreachable objective values. The approach was
                  tested with forests ranging from some dozens to more
                  than a thousand stands. In general, branch-and-bound
                  was able to quickly find optimal or good solutions,
                  even for medium/large instances.}
}
@proceedings{procICEC98,
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  year = 1998,
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}
@proceedings{procNOLTA2001,
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  year = 2001,
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@proceedings{zzz:DBLP:conf/fopara/2011,
  editor = {Ricardo Pe{\~n}a and Marko C. J. D. van Eekelen and
                  Olha Shkaravska},
  title = {Foundational and Practical Aspects of Resource
                  Analysis - Second International Workshop, FOPARA
                  2011, Madrid, Spain, May 19, 2011, Revised Selected
                  Papers},
  booktitle = {FOPARA},
  publisher = {Springer},
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  year = 2012,
  isbn = {978-3-642-32494-9},
  ee = {http://dx.doi.org/10.1007/978-3-642-32495-6},
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@proceedings{zzz:DBLP:conf/hm/2005,
  editor = {Maria J. Blesa and Christian Blum and Andrea Roli
                  and Michael Sampels},
  title = {Hybrid Metaheuristics, Second International
                  Workshop, HM 2005, Barcelona, Spain, August 29-30,
                  2005, Proceedings},
  booktitle = {Hybrid Metaheuristics},
  publisher = {Springer},
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@proceedings{zzz:DBLP:conf/lion/2012,
  editor = {Youssef Hamadi and Marc Schoenauer},
  title = {Learning and Intelligent Optimization - 6th
                  International Conference, LION 6, Paris, France,
                  January 16-20, 2012, Revised Selected Papers},
  booktitle = {LION},
  publisher = {Springer},
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  volume = 7219,
  year = 2012,
  isbn = {978-3-642-34412-1},
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@proceedings{zzz:DBLP:conf/mco/2008,
  editor = {Le Thi Hoai An and Pascal Bouvry and Pham Dinh Tao},
  title = {Modelling, Computation and Optimization in
                  Information Systems and Management Sciences, Second
                  International Conference, MCO 2008, Metz, France -
                  Luxembourg, September 8-10, 2008.  Proceedings},
  booktitle = {MCO},
  publisher = {Springer},
  series = {Communications in Computer and Information Science},
  volume = 14,
  year = 2008,
  isbn = {978-3-540-87476-8},
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@proceedings{zzz:DBLP:conf/nma/2010,
  editor = {Ivan Dimov and Stefka Dimova and Natalia
                  T. Kolkovska},
  title = {Numerical Methods and Applications - 7th
                  International Conference, NMA 2010, Borovets,
                  Bulgaria, August 20-24, 2010. Revised Papers},
  booktitle = {NMA},
  publisher = {Springer},
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  volume = 6046,
  year = 2011,
  isbn = {978-3-642-18465-9},
  ee = {http://dx.doi.org/10.1007/978-3-642-18466-6},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
@proceedings{zzz:DBLP:conf/ppsn/1996,
  editor = {Hans-Michael Voigt and Werner Ebeling and Ingo
                  Rechenberger and Hans-Paul Schwefel},
  title = {Parallel Problem Solving from Nature - PPSN IV,
                  International Conference on Evolutionary
                  Computation. The 4th International Conference on
                  Parallel Problem Solving from Nature, Berlin,
                  Germany, September 22-26, 1996, Proceedings},
  booktitle = {PPSN},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  volume = 1141,
  year = 1996,
  isbn = {3-540-61723-X},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
@proceedings{zzz:DBLP:conf/sls/2007,
  editor = {Thomas St{\"u}tzle and Mauro Birattari and Holger
                  H. Hoos},
  title = {Engineering Stochastic Local Search
                  Algorithms. Designing, Implementing and Analyzing
                  Effective Heuristics, International Workshop, SLS
                  2007, Brussels, Belgium, September 6-8, 2007,
                  Proceedings},
  booktitle = {SLS},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  volume = 4638,
  year = 2007,
  isbn = {978-3-540-74445-0},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

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