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首页> 外文期刊>European Journal of Operational Research >Lagrangian-relaxation-based solution procedures for a multiproduct capacitated facility location problem with choice of facility type
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Lagrangian-relaxation-based solution procedures for a multiproduct capacitated facility location problem with choice of facility type

机译:基于拉格朗日松弛的解决方案过程,用于选择设施类型的多产品受限设施位置问题

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This paper presents exact and heuristic solution procedures for a multiproduct capacitated facility location (MPCFL) problem in which the demand for a number of different product families must be supplied from a set of facility sites, and each site offers a choice of facility types exhibiting different capacities. MPCFL generalizes both the uncapacitated (or simple) facility location (UFL) problem and the pure-integer capacitated facility location problem. We define a branch-and-bound algorithm for MPCFL that utilizes bounds formed by a Lagrangian relaxation of MPCFL which decomposes the problem into UFL subproblems and easily solvable 0-1 knapsack subproblems. The UFL subproblems are solved by the dual-based procedure of Erlenkotter. We also present a subgradient optimization-Lagrangian relaxation-based heuristic for MPCFL. Computational experience with the algorithm and heuristic are reported. The MPCFL heuristic is seen to he extremely effective, generating solutions to the test problems that are on average within 2% of optimality, and the branch-and-bound algorithm is successful in solving all of the test problems to optimality.
机译:本文介绍了针对多产品功能限制的设施位置(MPCFL)问题的精确和启发式解决方案,在该问题中,必须从一组设施站点中满足对许多不同产品系列的需求,并且每个站点都提供了显示不同设施类型的选择能力。 MPCFL概括了无能力(或简单)设施位置(UFL)问题和纯整数能力设施位置问题。我们为MPCFL定义了分支定界算法,该算法利用MPCFL的拉格朗日松弛形成的边界,该边界将问题分解为UFL子问题和易于解决的0-1背包子问题。 UFL子问题通过Erlenkotter的双重过程解决。我们还为MPCFL提出了次梯度优化-基于拉格朗日松弛法的启发式算法。报告了该算法的计算经验和启发式方法。 MPCFL启发式方法非常有效,它可以为平均平均在最优性2%之内的测试问题生成解决方案,而分支定界算法可以成功地将所有测试问题均最优化。

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