Title: Network optimisation design of Hazmat based on multi-objective genetic algorithm under the uncertain environment

Authors: Changxi Ma

Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China

Abstract: To avoid the hazardous material (Hazmat) transportation accidents, it is necessary to design the Hazmat transportation network in advance. Due to the uncertainty of risks and time during the Hazmat transportation, the paper studies the optimal network design method under the uncertain environment. The transportation scenario is divided into two types including single-vehicle centralised service and multi-vehicle coordinated service. The opportunity constrained programming model for the optimal design of Hazmat transportation network is constructed and the improved multi-objective genetic algorithm is used to solve the model. The case study shows the opportunity constrained programming model can better describe the optimal design of Hazmat transportation network than the traditional method under the uncertain environment. The repeating computer simulation tests show the proposed improved multi-objective genetic algorithm is feasible.

Keywords: optimisation; transportation network; multi-objective genetic algorithm; Pareto solution; hazmat transportation.

DOI: 10.1504/IJBIC.2018.096482

International Journal of Bio-Inspired Computation, 2018 Vol.12 No.4, pp.236 - 244

Received: 18 Apr 2018
Accepted: 28 Jul 2018

Published online: 29 Nov 2018 *

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