Title: Memetic grey wolf optimiser algorithm for solving the cumulative CVRP

Authors: Yanguang Cai; Gewen Huang; Yuanhang Qi; Helie Huang; Yunjian Xu

Addresses: School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, 510006, China ' Information and Network Centre, Jiaying University, Meizhou, Guangdong, 514015, China ' School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China ' Guangdong Science and Technology Infrastructure Centre, Guangzhou, Guangdong, 510033, China ' School of Intelligent Engineering, Guangdong AIB Polytechnic, Guangzhou, Guangdong, 510507, China

Abstract: The cumulative capacitated vehicle routing problem (CCVRP) is a variation in the vehicle routing problem that aims to minimise the waiting time of all clients. This paper proposes a memetic grey wolf optimiser algorithm (MGWOA) to solve this problem. A bidirectional conversion strategy based on grouping and combining is proposed to realise the conversion between grey wolf positions and vehicle routing groups. The neighbourhood search optimisation strategy with roulette wheel selection and the continual optimisation strategy for optimal solutions based on routing reconstruction are proposed to optimise the routing group. The experimental results show that: the MGWOA proposed can effectively solve the CCVRP problems; the solving accuracy and stability of the proposed algorithm were verified by comparison with five other meta-heuristic algorithms; the bidirectional conversion strategy, the neighbourhood search optimisation strategy, and the continual optimisation strategy proposed improve the convergence speed and the convergence accuracy of the MGWOA.

Keywords: vehicle routing; memetic; GWO; grey wolf optimiser; bidirectional conversion; neighbourhood search; roulette wheel selection; continual optimisation; routing reconstruction; swarm intelligence.

DOI: 10.1504/IJAACS.2023.134844

International Journal of Autonomous and Adaptive Communications Systems, 2023 Vol.16 No.6, pp.513 - 535

Received: 31 Dec 2020
Accepted: 04 Oct 2021
Published online: 14 Nov 2023 *

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