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A New Method to Solve the Multi Traveling Salesman Problem with the Combination of Genetic Algorithm and Clustering Technique

机译:遗传算法与聚类技术相结合的多旅行商问题求解新方法

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The multi traveling salesman problem is the extension of the well-known problem of traveling salesman and considered as a NP-Complete problem having exponential solution space. MTSP is more complicated than TSP, because in MTSP first the cities must be divided between salesmen, and then the optimal order of cities for each traveling salesman should be determined. By looking at early studies, it is revealed that researchers had focused on MTSP less than TSP, and few studies have been done in this area so far. In this paper a new combinatorial algorithm named CGA-MTSP is proposed for solving MTSP problem which is a combination of Genetic Algorithm and Clustering Technique. The aim of this method is to reduce the travelled distance by salesmen. In the proposed method the Clustering Technique has been used intelligently to reduce the solution space of the mentioned problem. Experimental results show that the proposed algorithm (CGA-MTSP) leads to better results than other algorithms, but it requires more execution time.
机译:多重旅行推销员问题是旅行推销员的已知问题的扩展,被认为是具有指数解空间的NP-完全问题。 MTSP比TSP更为复杂,因为在MTSP中,首先必须将城市划分为推销员,然后才能确定每个旅行推销员的城市最佳顺序。通过查看早期研究,可以发现研究人员对MTSP的关注少于对TSP的关注,到目前为止,在这一领域的研究很少。针对遗传算法和聚类技术相结合的问题,提出了一种新的组合算法CGA-MTSP。这种方法的目的是减少销售人员的行进距离。在提出的方法中,聚类技术已被智能地用于减少所提到问题的解决空间。实验结果表明,所提出的算法(CGA-MTSP)比其他算法具有更好的结果,但是需要更多的执行时间。

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