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http://dx.doi.org/10.7232/JKIIE.2011.37.2.124

Adaptive Mean Value Cross Decomposition Algorithms for Capacitated Facility Location Problems  

Kim, Chul-Yeon (Department of Industrial Engineering, Hanyang University)
Choi, Gyung-Hyun (Graduate School of Technology and Innovation Management, Hanyang University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.37, no.2, 2011 , pp. 124-131 More about this Journal
Abstract
In this research report, we propose a heuristic algorithm with some primal recovery strategies for capacitated facility location problems (CFLP), which is a well-known combinatorial optimization problem with applications in distribution, transportation and production planning. Many algorithms employ the branch-and-bound technique in order to solve the CFLP. There are also some different approaches which can recover primal solutions while exploiting the primal and dual structure simultaneously. One of them is a MVCD (Mean Value Cross Decomposition) ensuring convergence without solving a master problem. The MVCD was designed to handle LP-problems, but it was applied in mixed integer problems. However the MVCD has been applied to only uncapacitated facility location problems (UFLP), because it was very difficult to obtain "Integrality" property of Lagrangian dual subproblems sustaining the feasibility to primal problems. We present some heuristic strategies to recover primal feasible integer solutions, handling the accumulated primal solutions of the dual subproblem, which are used as input to the primal subproblem in the mean value cross decomposition technique, without requiring solutions to a master problem. Computational results for a set of various problem instances are reported.
Keywords
Capacitated Facility Location Problem; Cross Decomposition; Mean Value Cross Decomposition; Primal Recovery Strategies; Lagrangian Relaxation; Heuristics;
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