一类新的限时旅行商问题的遗传算法求解

Moumita Mondal, D. Srivastava
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引用次数: 1

摘要

在本文中,作者解释了一个时间限制的旅行商问题(TSP),其中每个城市都有一个时间限制。旅行者必须在预定的时间限制(每个城市都是固定的)内或之前到达每个城市。旅行成本也是该模型的一个参数。这个时间限制表示旅行者必须到达某个特定城市的最长时间单位。在这里,交通费用是问题的目标。此外,对于一次完整的旅行,总旅行时间也是固定的。这项研究最近为每个城市引入了这个时间限制。提出了一种基于遗传算法的TSP求解方法。将循环交叉和特殊突变操作应用于遗传算法求解TSP。为了证明该算法的有效性,作者考虑了一些基准实例。然后,作者为提出的TSP重新定义了几个基准实例。给出了不同数据集下的计算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Genetic Algorithm-Based Approach to Solve a New Time-Limited Travelling Salesman Problem
In this paper, the authors have explained a time limited travelling salesman problem (TSP) where a time limit is associated with each city. The traveller must reach each city on or before the predetermined time limit (that is fixed for each city) in his/her tour. Travel cost is also a parameter for the proposed model. This time limit indicates the maximum time unit by which the traveller must reach a particular city. Here, travel cost is the objective of the problem. Moreover, total travel time is also fixed for a complete tour. This research recently introduced this time limit for each of the cities. The proposed TSP is solved by using a genetic algorithm-based method. The cyclic crossover and special mutation operations have been adapted to GA for solving the proposed TSP. To show the effectiveness of proposed algorithm, the authors have considered some benchmark instances. Then the authors redefine a few benchmark instances for the proposed TSP. Computational results with different data sets are presented.
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