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A Branch-and-Cut algorithm for the Single Source Capacitated Facility Location problem

机译:单源容量设施定位问题的分支剪切算法

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Several Mixed Integer Linear Programming problems present a formulation based on a great number of knapsack constraints. Problems widely addressed in literature with this structure are, among others, Generalized Assignment, Multiple Knapsack, Bin Packing, Capacitated P-median and Single Source Capacitated Facility Location. In general knapsack constraints make these problems very hard to solve. The state of the art on these problems requires to use approaches besed on Lagrangean Relaxation or decomposition approaches like Dantzig-Wolfe and Column Generation tenchniques. In this paper, we present an approach based on the generation of general cutting planes of the polyhedron associated with each knapsack constraints. This approach yelds a lower bound for the LP-relaxation that is the same obtained by the Dantzig-Wolfe decomposition and henceforth stronger than the LP-relaxation. We use this aproach in the solution of the Single Source Capacitated Facility Location problem (SSCFLP) using a Branch-and-Cut algorithm. Computational experience is reported on a large set of test instances available in literature.
机译:几个混合整数线性规划问题提出了一个基于大量背包约束的公式。具有这种结构的文献中广泛解决的问题包括:广义分配,多重背包,装箱,带容量的P中值和带容量的单个源设施。通常,背包约束使这些问题很难解决。这些问题的最新技术要求使用拉格朗日弛豫或分解方法(如Dantzig-Wolfe和Column Generation tenchniques)上的方法。在本文中,我们提出一种基于与每个背包约束相关联的多面体的通用切割平面的生成的方法。这种方法为LP松弛产生了下限,该下限与通过Dantzig-Wolfe分解获得的下界相同,此后比LP松弛更强。我们在使用分支剪切算法的单源容量设施定位问题(SSCFLP)的解决方案中使用此方法。关于计算经验的报道涉及大量文献中提供的测试实例。

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