Tree search for the Number Partitioning Problem =============================================== Author: Joao Pedro Pedroso and Mikio Kubo < > Date: 2009/01/09 10:57:04 Table of Contents ================= 1 BENCHMARK INSTANCES 2 PROGRAM FILES 3 OUTPUT OF COMPUTATIONAL EXPERIMENT 1 BENCHMARK INSTANCES ~~~~~~~~~~~~~~~~~~~~~ --------------------- * [easy.zip] - contains =easy*.dat= instances: random data with under-critical number of bits. * [hard.zip] - contains =hard*.dat= instances: random data with over-critical number of bits. Notice that most of the numbers do not fit in a 32 or 64 bit integer. * [D.zip] - contains files for decimal instances =nNNNdDDeXX.dat=, were each number corresponds to =DD= digits drawn uniformely from {0,...9}; instances have =NNN= elements. For each pair =NNN,DD= there are 10 independent instance (=XX= digits). Files were generated with [npp_mk_inst.py], using:\\ Python 2.4.4 (#2, Jan 3 2008, 13:36:28) \\ [GCC 4.2.3 20071123 (prerelease) (Debian 4.2.2-4)] on linux2 2 PROGRAM FILES ~~~~~~~~~~~~~~~ --------------- * [npp.py] heuristics for the NPP * [npp_dfs.py] tree search, based on depth-first search * [npp_bfs.py] tree search, based on breadth-first search * [graphtools.py] auxiliary file (generic tools for dealing with graphs) * [npp_run_dfs.py] run complete experiment with depth-first search * [npp_run_bfs.py] run complete experiment with breadth-first search * [npp_mk_inst.py] program used to produce the instance files 3 OUTPUT OF COMPUTATIONAL EXPERIMENT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ------------------------------------ * [npp_bfs.csv] main results for breadth-first * [npp_bfs.log] standard output log for breadth-first * [npp_dfs.csv] main results for breadth-first * [npp_dfs.log] standard output log for breadth-first * [npp_dfs_interrupted.log] standard output log for the interrupted runs with breadth-first