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A new grouping genetic algorithm approach to the multiple traveling salesperson problem

机译:多重旅行商问题的一种新的分组遗传算法

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The multiple traveling salesperson problem (MTSP) is an extension of the well known traveling salesperson problem (TSP). Given m > 1 salespersons and n > m cities to visit, the MTSP seeks a partition of cities into m groups as well as an ordering among cities in each group so that each group of cities is visited by exactly one salesperson in their specified order in such a way that each city is visited exactly once and sum of total distance traveled by all the salespersons is minimized. Apart from the objective of minimizing the total distance traveled by all the salespersons, we have also considered an alternate objective of minimizing the maximum distance traveled by any one salesperson, which is related with balancing the workload among salespersons. In this paper, we have proposed a new grouping genetic algorithm based approach for the MTSP and compared our results with other approaches available in the literature. Our approach outperformed the other approaches on both the objectives.
机译:多重旅行商问题(MTSP)是众所周知的旅行商问题(TSP)的扩展。给定m> 1个销售人员和n> m个要访问的城市,MTSP会将城市划分为m个组,并按城市在每个组中的顺序进行排序,以使每个城市组仅由一个销售人员按其指定顺序进行访问。这样一来,每个城市只需访问一次,所有销售人员所走的总距离之和就可以最小化。除了最小化所有销售人员的总行驶距离的目标之外,我们还考虑了另一种目标,即最小化任何一个销售人员的最大行驶距离,这与平衡销售人员之间的工作量有关。在本文中,我们为MTSP提出了一种基于分组遗传算法的新方法,并将我们的结果与文献中提供的其他方法进行了比较。在两个目标上,我们的方法都优于其他方法。

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