Truck and Trailer Routing Problem Solving by a Backtracking Search Algorithm

Yuan Shiyi (), Fu Jianwen (), Cui Feng () and Zhang Xin ()
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Yuan Shiyi: School of Economics and Management, Beijing University of Technology, Beijing, 100124, China
Fu Jianwen: School of Economics and Management, Beijing University of Technology, Beijing, 100124, China
Cui Feng: Research Department of Beijing Smarter Eye Technology Co., Ltd, Beijing, 100123, China
Zhang Xin: Institute of Fundamental and Interdisciplinary Sciences, Beijing Union University, Beijing, 100101, China

Journal of Systems Science and Information, 2020, vol. 8, issue 3, 253-272

Abstract: Truck and trailer routing problem (TTRP) is one of the most frequently encountered problem in city distribution, particularly in populated and intensive downtown. This paper addresses this problem and designs a novel backtracking search algorithm (BSA) based meta-heuristics to solve it. The initial population is created by T-sweep heuristic and then based on the framework of backtracking search algorithm, four types of route improvement strategies are used as building blocks to improve the solutions of BSA in the process of mutation and crossover. The computational experiments and results indicate that the proposed BSA algorithm can provide an effective approach to generate high-quality solutions within the satisfactory computational time.

Keywords: backtracking search algorithm; evolutionary optimization techniques; truck and trailer; vehicle routing (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:8:y:2020:i:3:p:253-272:n:4

DOI: 10.21078/JSSI-2020-253-20

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