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Single-Source Capacitated Multi-Facility Weber Problem-An iterative two phase heuristic algorithm

机译:单源容量多设施Weber问题-迭代两阶段启发式算法

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Multi-Facility Weber Problem (MFWP), also known as continuous location-allocation problem, entails determining the locations of a predefined number of facilities in a planar space and their related customer allocations. In this paper, we focus on a new variant of the problem known as Single-Source Capacitated MFWP (SSCMFWP). To tackle the problem efficiently and effectively, an iterative two-phase heuristic algorithm is put forward. At the phase I, we aim to determine proper locations for facilities, and during the phase II, assignment of customers to these facilities is pursued. As an alternative solution method, a simulated annealing (SA) algorithm is also proposed for carrying out the phase 1. The proposed algorithms are validated on a comprehensive set of test instances taken from the literature. The proposed iterative two-phase algorithm produces superior results when assessed against the proposed SA algorithm as well as a general MINLP Solver known as BARON. The latter is applied to produce optimal solutions for small sized instances and generate upper bound for medium ones.
机译:多设施韦伯问题(MFWP),也称为连续位置分配问题,需要确定平面空间中预定义数量的设施的位置及其相关的客户分配。在本文中,我们关注于称为单源电容式MFWP(SSCMFWP)的问题的新变体。为有效解决这一问题,提出了一种迭代两阶段启发式算法。在第一阶段,我们旨在确定设施的正确位置,在第二阶段,我们将客户分配给这些设施。作为一种替代解决方案方法,还提出了一种模拟退火(SA)算法来执行第1阶段。所提出的算法在从文献中获得的一组全面的测试实例上得到了验证。当与建议的SA算法以及称为BARON的常规MINLP求解器进行比较时,建议的迭代两阶段算法产生了更好的结果。后者用于为小型实例生成最佳解决方案,并为中等实例生成上限。

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