Mathematical Optimization
Solving Problems using Gurobi and Python
Mathematical Optimization
Solving Problems using Gurobi and Python
SOURCE CODE FOR THE Models used:
Kubo, Pedroso, Muramatsu and Rais
In this page we report results obtained using Python/Gurobi models for solving several well-known problems. The computational setup was the following:
•Python version: 2.6.6
•Gurobi version: 5.0.1
•Computer characteristics:
- Intel(R) Xeon(R) CPU E5-2687W 0 @ 3.10GHz
- RAM: 64 GB
- CPU usage limited to one thread
Case studies:
1.Knapsack problem:
Multi-constraint knapsack problem
2.Location
Facility location problem -- ORLIB instances
Facility location problem -- random instances
Comparison of k-median, k-center, and binary search with k-cover
Nonlinear facility location problem
3.Graph problems
4.Routing
Asymmetric traveling salesman problem
Traveling salesman problem with time windows
5.Scheduling
Scheduling with linear ordering formulation, time index formulation, and disjunctive formulation
6.Lot sizing problem
Lot sizing using Trigeiro's-like instances
7.Piecewise linear approximation of nonlinear functions
Nonlinear facility location problem
9.Second-order cone optimization