Modified Genetic Algorithm with Flexible Crossover for the Capacitated Electric Vehicle Routing Problem

dc.contributor.authorAjchara Phu-ang
dc.contributor.authorArit Thammano
dc.date.accessioned2026-05-08T19:16:55Z
dc.date.issued2023-10-26
dc.description.abstractThis paper proposed a modification of genetic algorithm with a new technique called the flexible crossover operation for solving the capacitated electric vehicle routing problem (CEVRP). The framework of this paper is based on the concept of the classic genetic algorithm (GA). To improve the performance of the genetic algorithm, two aspects have been proposed, 1) The Pre-Post mutation is present to obtain the ability of local search capacities. 2) The flexible crossover operation is proposed to enhance the diverse capabilities. The proposed algorithm has been evaluated and compared to the state-of-the-art algorithms. The experimental result on seven data sets demonstrated that the proposed algorithm is effective for solving a small and medium data set of capacitated electric vehicle routing problem.
dc.identifier.doi10.1109/icitee59582.2023.10317770
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15773
dc.subjectVehicle Routing Optimization Methods
dc.subjectMetaheuristic Optimization Algorithms Research
dc.subjectAdvanced Multi-Objective Optimization Algorithms
dc.titleModified Genetic Algorithm with Flexible Crossover for the Capacitated Electric Vehicle Routing Problem
dc.typeArticle

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