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Fuzzy logic based algorithms for maximum covering location problems

机译:基于模糊逻辑的算法最大覆盖位置问题

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This paper concerns a class of maximum covering location problems in networks in uncertain environments. It is assumed that (a) relative weights of demand nodes are either deterministic or imprecise, described by linguistic expressions and (b) potential facility site locations are limited to network nodes. The concept of coverage is extended to include a degree of node coverage which means that the borders between the subset of covered demand nodes and the subset of uncovered demand nodes are inexact. The acceptable service distance/travelling times from a facility site to demand nodes are modelled by fuzzy sets. Three new algorithms for choosing the best facility locations are developed which assume that (1) demands at all nodes are equally important, (2) relative weights of demand at nodes are deterministic and (3) weights of demand at nodes are imprecise and described by linguistic terms, respectively. The algorithms are based on searching among potential facility nodes by applying comparison operations on discrete fuzzy sets. It is shown how to extend the proposed algorithms from one-site to multi-site covering problems. Illustrative examples of selecting locations for logistics centres in a distribution company are given.
机译:本文涉及不确定环境中网络中的一类最大覆盖位置问题。假设(a)需求节点的相对权重是确定性的或不精确的,由语言表达式描述,并且(b)潜在的设施站点位置仅限于网络节点。覆盖的概念被扩展为包括一定程度的节点覆盖,这意味着覆盖的需求节点的子集和未覆盖的需求节点的子集之间的边界不精确。从设施站点到需求节点的可接受服务距离/旅行时间通过模糊集建模。开发了三种用于选择最佳设施位置的新算法,这些算法假设(1)所有节点上的需求同等重要,(2)节点上的相对需求权重是确定性的,并且(3)节点上的需求权重是不精确的,并由语言术语。该算法基于通过对离散模糊集进行比较运算而在潜在设施节点之间进行搜索。它显示了如何将所提出的算法从一站式扩展到多站式覆盖问题。给出了在配送公司中选择物流中心位置的说明性示例。

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