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首页> 外文期刊>Studies in Informatics and Control >Combining Tabu Search and Genetic Algorithms to Solve the Capacitated Multicommodity Network Flow Problem
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Combining Tabu Search and Genetic Algorithms to Solve the Capacitated Multicommodity Network Flow Problem

机译:禁忌搜索和遗传算法相结合解决多商品网络的容量问题

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摘要

Network design has been an important issue in logistics during the last century. This is due to the significant impact that an efficient distribution network design can have over both costs and service level. In this article, we present a heuristic solution approach for the well-known capacitated multicommodity network flow problem. The heuristic approach combines two well-known algorithms namely Tabu Search and Genetic Algorithms. While the main algorithm is Tabu Search, the Genetic Algorithm is used to select the best option among the neighbours of the current solution. To be able to do that some well-known evolutionary operators such as cross-over and mutation are made use of. This hybrid approach obtains important improvements when compared to the ones presented previously in the literature.
机译:在上个世纪,网络设计一直是物流中的重要问题。这是由于有效的配电网络设计可能对成本和服务水平产生重大影响。在本文中,我们提出了一种启发式解决方案,用于解决著名的电容式多商品网络流量问题。启发式方法结合了两个著名的算法,即禁忌搜索和遗传算法。主要算法是禁忌搜索,而遗传算法用于在当前解决方案的邻居中选择最佳选项。为了做到这一点,利用了一些著名的进化算子,例如交叉和变异。与先前文献中介绍的方法相比,这种混合方法获得了重要的改进。

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