A new modeling and solution approach for the set-partitioning problem
Computers and Operations Research
A Relax-and-Cut algorithm for the set partitioning problem
Computers and Operations Research
Grid-Enabled Optimization with GAMS
INFORMS Journal on Computing
A Generalized Wedelin Heuristic for Integer Programming
INFORMS Journal on Computing
A dual ascent procedure for the set partitioning problem
Discrete Optimization
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We describe a parallel, linear programming and implication-based heuristic for solving set partitioning problems on distributed memory computer architectures. Our implementation is carefully designed to exploit parallelism to greatest advantage in advanced techniques like preprocessing and probing, primal heuristics, and cut generation. A primaldual subproblem simplex method is used for solving the linear programming relaxation, which breaks the linear programming solution process into natural phases from which we can exploit information to find good solutions on the various processors. Implications from the probing operation are shared among the processors. Combining these techniques allows us to obtain solutions to large and difficult problems in a reasonable amount of computing time.