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首页> 外文期刊>International Journal of Information Technology & Decision Making >A GROUPING GENETIC ALGORITHM FOR THE MULTIPLE TRAVELING SALESPERSON PROBLEM
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A GROUPING GENETIC ALGORITHM FOR THE MULTIPLE TRAVELING SALESPERSON PROBLEM

机译:多重旅行商问题的分组遗传算法

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The multiple traveling salesperson problem (MTSP) involves scheduling m > 1 salespersons to visit a set of n >m locations. Thus, the n locations must be divided into m groups and arranged so that each salesperson has an ordered set of cities to visit. The grouping genetic algorithm (GGA) is a type of genetic algorithm (GA) designed particularly for grouping problems. It has been successfully applied to a variety of grouping problems. This paper focuses on the application of a GGA to solve the MTSP. Our GGA introduces a new chromosome representation to indicate which salesperson is assigned to each tour and the ordering of the cities within each tour. We compare our method to standard GAs that employ either the one-chromosome or two-chromosome representation for MTSP. This research demonstrates that our GGA with its new chromosome representation is capable of solving a variety of MTSP problems from the literature and can outperform the traditional encodings of previously published GA methods.
机译:多重旅行推销员问题(MTSP)涉及安排m> 1个推销员来访问一组n> m个位置。因此,必须将n个地点分为m个组并进行排列,以使每个销售人员都有一组要访问的有序城市。分组遗传算法(GGA)是专门为分组问题设计的一种遗传算法(GA)。它已成功应用于各种分组问题。本文重点介绍了GGA在解决MTSP中的应用。我们的GGA引入了一种新的染色体表示法,以指示分配给每个游览的销售人员以及每个游览中城市的顺序。我们将我们的方法与采用单染色体或双染色体表示的MTSP的标准GA进行了比较。这项研究表明,我们的GGA具有新的染色体表示能力,能够解决文献中的多种MTSP问题,并且性能优于以前发布的GA方法的传统编码。

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