A multi-objective imperialist competitive algorithm to solve a new multi-modal tree hub location problem

R. Tavakkoli-Moghaddam, S. Sedehzadeh
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引用次数: 5

Abstract

A hub location problem is a main group of the transportation network, which is utilized as a connecting and switching point for demand between origins and destinations. Recently, a tree hub location problem has been introduced as an incomplete hub network with single assignment, in which hubs are connected by means of a tree. This paper presents a new bi-objective, multi-modal tree hub location problem with different capacity levels. Besides the location and allocation decisions in tree hub network, this model decides on transportation modes and capacity levels such that the total transportation cost and time are minimized. Additionally, a multi-objective imperialist competitive algorithm (MOICA) is proposed to solve the presented model and obtain Pareto-optimal solutions of the given problem. Finally, the performance of this algorithm is compared with a non-dominated sorting genetic algorithm (NSGA-II).
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一种求解新型多模态树形枢纽定位问题的多目标帝国竞争算法
枢纽位置问题是交通网络的一个主要问题,它被用作起点和目的地之间需求的连接和切换点。近年来,树型枢纽定位问题被引入到单分配的不完全枢纽网络中,其中枢纽通过树的方式连接。提出了一种新的双目标、多模式、不同容量水平的树状枢纽定位问题。除了树形枢纽网络中的位置和分配决策外,该模型还决定了运输方式和容量水平,以使总运输成本和总运输时间最小。此外,提出了一种多目标帝国主义竞争算法(MOICA)来求解所提出的模型并获得给定问题的pareto最优解。最后,将该算法的性能与非支配排序遗传算法(NSGA-II)进行了比较。
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