An Evolutionary Algorithm with Heuristic Longest Cycle Crossover for Solving the Capacitated Vehicle Routing Problem

Thammarsat Visutarrom, Tsung Che Chiang

研究成果: 書貢獻/報告類型會議貢獻

摘要

Crossover is one of the most important parts of an evolutionary algorithm (EA) for solving optimization problems. Many crossover operators have been proposed for solving the capacitated vehicle routing problem (CVRP), a classical NP-hard problem in the field of operations research. This paper aims to improve the search ability of the cycle crossover (CX). The longest cycle selection and the nearest neighbor heuristic are utilized to improve the performance. Experimental results show that the proposed heuristic longest cycle crossover (HLCX) outperforms the original CX and four other operators. Additionally, we apply a search reduction strategy in the local refinement procedure to reduce the computation time at a little cost of solution quality.

原文英語
主出版物標題2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面673-680
頁數8
ISBN(電子)9781728121536
DOIs
出版狀態已發佈 - 2019 六月
事件2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, 新西兰
持續時間: 2019 六月 102019 六月 13

出版系列

名字2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

會議

會議2019 IEEE Congress on Evolutionary Computation, CEC 2019
國家新西兰
城市Wellington
期間19/6/1019/6/13

ASJC Scopus subject areas

  • Computational Mathematics
  • Modelling and Simulation

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    Visutarrom, T., & Chiang, T. C. (2019). An Evolutionary Algorithm with Heuristic Longest Cycle Crossover for Solving the Capacitated Vehicle Routing Problem. 於 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (頁 673-680). [8789946] (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2019.8789946