Title: Vehicle routing multi-objective optimisation for hazardous materials transportation based on adaptive double populations genetic algorithm

Authors: Changxi Ma; Ruichun He; Chengming Zhu; Xinfeng Yang; Fuquan Pan

Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' Transportation Research Center, Beijing University of Technology, Beijing City, 100124, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Automobile and Traffic, Qingdao Technological University, Qingdao, 266520, China

Abstract: Aiming at hazardous materials transportation (HMT), vehicle routing optimisation models for single vehicle and multiple vehicle are proposed respectively, and the adaptive double populations genetic algorithm are constructed. Firstly, the goal functions of models are minimising the total risk, cost and the running time of hazardous materials vehicle. Then, the load constraint, max-risk constraint and time window constraint are considered. Finally, natural number is used for coding, double populations mechanism and adaptive weighted fitness allocation mechanism are adopted to calculate unit fitness, partial matched-crossover method is adopted for crossover operation, and the inversion mutation operator is adopted for mutation operation. Case study shows the model and algorithm are feasible, the vehicle routing strategy can provide direct reference for hazardous materials transportation decision-making departments and it is an effective way for prevention of hazardous materials transportation accidents.

Keywords: optimisation; vehicle routing problem; VRP; improved genetic algorithm; hazardous materials.

DOI: 10.1504/IJICA.2017.088160

International Journal of Innovative Computing and Applications, 2017 Vol.8 No.4, pp.198 - 206

Received: 15 Apr 2016
Accepted: 21 Jun 2016
Published online: 27 Nov 2017 *

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