Half Open Multi-Depot Heterogeneous Vehicle Routing Problem for Hazardous Materials Transportation

Zhongxin Zhou, Minghu Ha, Hao Hu and Hongguang Ma
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Zhongxin Zhou: School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China
Minghu Ha: School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China
Hao Hu: School of Economics and Management, Shijiazhuang Tiedao University, Shijiazhuang 050000, China
Hongguang Ma: School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China

Sustainability, 2021, vol. 13, issue 3, 1-17

Abstract: How to reduce the accidents of hazardous materials has become an important and urgent research topic in the safety management of hazardous materials. In this study, we focus on the half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. The goal is to determine the vehicle allocation and the optimal route with minimum risk and cost for hazardous materials transportation. A novel transportation risk model is presented considering the variation of vehicle loading, vehicle types, and hazardous materials category. In order to balance the transportation risk and the transportation cost, we propose a bi-objective mixed integer programming model. A hybrid intelligent algorithm is developed based on the ε-constraint method and genetic algorithm to obtain the Pareto optimal solutions. Numerical experiments are provided to demonstrate the effectiveness of the proposed model. Compared with the close multi-depot heterogeneous vehicle routing problem, the average risk and cost obtained by the proposed bi-objective mixed integer programming model can be reduced by 3.99% and 2.01%, respectively. In addition, compared with the half open multi-depot homogeneous vehicle routing problem, the cost is significantly reduced with the acceptable risk.

Keywords: hazardous materials transportation; half open multi-depot heterogeneous vehicle routing problem; bi-objective mixed integer programming model; hybrid intelligent algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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