Evolutionary Algorithm Based on Partition Crossover (EAPX) for the Vehicle Routing Problem

Takwa Tlili, F. Chicano, S. Krichen, E. Alba
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引用次数: 1

Abstract

Problems associated with seeking the lowest cost vehicle routes to deliver demand to customers are called Vehicle Routing Problems (VRPs). Over the last decades, increasing research efforts are being dedicated to handle the VRPs. Most of the solution approaches have been metaheuristics, such as the evolutionary algorithms (EAs). This paper proposes a new EA (EAPX) based on Partition Crossover (PX), a recombination operator proposed by Whitley et al., which demonstrated very good performance in solving the Traveling Salesman Problem (TSP). PX strength lies in the characteristic of tunneling between local optima: if the parents are both local optima, with a high probability PX will generate two local optima offspring. Experimentations show that EAPX is competitive with the existing solution approaches.
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基于分区交叉的车辆路径进化算法
寻找成本最低的车辆路线将需求交付给客户的问题被称为车辆路线问题(vrp)。在过去的几十年里,越来越多的研究工作致力于处理vrp。大多数解决方法都是元启发式的,例如进化算法(EAs)。本文提出了一种新的基于分割交叉算子(PX)的EA (EAPX),该算子是Whitley等人提出的重组算子,在求解旅行商问题(TSP)中表现出了很好的性能。PX的强度在于局部最优之间的隧穿特性:如果双亲都是局部最优,则PX有很大概率会产生两个局部最优子代。实验表明,EAPX与现有的求解方法相比具有一定的竞争力。
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