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A combined Lagrangian, linear programming, and implication heuristic for large-scale set partitioning problems

✍ Scribed by A. Atamtürk; G. L. Nemhauser; M. W. P. Savelsbergh


Publisher
Springer US
Year
1996
Tongue
English
Weight
685 KB
Volume
1
Category
Article
ISSN
1381-1231

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✦ Synopsis


Given a finite ground set, a set of subsets, and costs on the subsets, the set partitioning problem is to find a minimum cost partition of the ground set. Many combinatorial optimization problems can be formulated as set partitioning problems. We present an approximation algorithm that produces high-quality solutions in an acceptable amount of computation time. The algorithm is iterative and combines problem size-reduction techniques, such as logical implications derived from feasibility and optimality conditions and reduced cost fixing, with a primal heuristic based on cost perturbations embedded in a Lagrangian dual framework, and cutting planes. Computational experiments illustrate the effectiveness of the approximation algorithm.