A credibilistic mixed integer programming model for time-dependent hazardous materials vehicle routing problem

Hazardous materials are harmful to environment and human health due to their toxic ingredients. It is very important to intensify efforts in the safety management of hazardous materials, and fundamentally prevent and reduce accidents. In this study, we consider a time-dependent hazardous materials vehicle routing problem in a two-echelon supply chain system. The goal is to determine the departure time and the optimal route with a minimum risk value for hazardous materials transportation. Considering that time has a signicant influence on the transportation risk, we formulate a time-dependent transportation risk model and propose a credibilistic mixed integer programming model to minimize the expected risk. An improved genetic algorithm whose chromosomes contain two types of genes is designed to handle the proposed model. Numerical experiment is given to illustrate the efficiency of the proposed model and algorithm. Compared with the traditional transportation risk model, the time-dependent transportation risk model can signicantly reduce the risk around 42%.