Title: Separated vehicle scheduling optimisation for container trucking transportation based on hybrid quantum evolutionary algorithm

Authors: Zheng Wang; Jianfeng Dai

Addresses: Department of Computer Engineering, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou, China ' Department of Computer Engineering, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou, China

Abstract: To optimise the trucking problem with time windows, a multi-objective mathematical programming model was established for separated vehicle scheduling. To compute Pareto solutions, a phased optimal algorithm based on hybrid quantum evolution was put forward. To enhance the convergence rate, a greedy repair operator was designed. To avoid premature convergence, a neighbourhood search based on node switching was performed. To maintain the dispersion of the Pareto solutions, an adaptive grid operator was designed. The effectiveness of the proposed method compared to previous scheduling modes and other algorithms was verified experimentally. For the same transport capacity, the vehicle scheduling method based on a quantum evolutionary algorithm can greatly reduce both the number of vehicles and cost.

Keywords: tractor and trailer separated; Pareto optimal solutions; truck and trailer routing problem; TTRP; hybrid quantum evolutionary algorithm.

DOI: 10.1504/IJCSM.2017.088013

International Journal of Computing Science and Mathematics, 2017 Vol.8 No.5, pp.405 - 413

Received: 30 Jul 2016
Accepted: 08 May 2017
Published online: 14 Nov 2017 *

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