Title: A hyper-heuristic algorithm for VRP problem and its application in highway construction

Authors: Wen Zhong; Zhijun Xie; Mai Li; Qi Zhang; Shaomiao Chen

Addresses: Hunan Pingyi Expressway Construction and Development Co. Ltd., Yueyang, China ' Hunan Pingyi Expressway Construction and Development Co. Ltd., Yueyang, China ' Hunan Communications Research Institute Co. Ltd., Changsha, China ' Hunan Key Laboratory of Service Computing and New Software Service Technology, School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China ' Hunan Key Laboratory of Service Computing and New Software Service Technology, School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China

Abstract: Many problems can be described as vehicle routing problems (VRPs) in engineering applications. More and more scholars have been paying attention to VRP optimisation in recent years, especially for large-scale VRPs, with the development of logistics business. In this paper, a hyper-heuristic algorithm for large-scale VRPs is proposed. It uses the diversity of strategic space to improve the diversity of algorithms. In contrast, most of the current VPR optimisation methods only pay attention to the characteristics of solution space. The proposed algorithm consists of two layers, a high-level heuristic selection strategy and a low-level heuristic policy pool. The higher-level strategy adjusts the algorithm's weight and guides the search direction dynamically based on the historical performance of the lower-level local search strategy. Simulation experiments show that, compared to the other two state-of-the-art algorithms, the proposed algorithm is more stable and performs more efficiently under most GWKC instances. Additionally, the proposed algorithm is practically applied to a material distribution problem in highway construction, and better performance is achieved.

Keywords: vehicle routing problem; VPR; hyper-heuristic algorithm; HHA; highway construction; large scale optimisation.

DOI: 10.1504/IJES.2023.136390

International Journal of Embedded Systems, 2023 Vol.16 No.2, pp.143 - 152

Received: 17 May 2023
Accepted: 07 Aug 2023
Published online: 31 Jan 2024 *

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