Bi-level chance constraint programming model for hazardous materials distribution

Abstract

With the growing presence of hazardous materials in daily life, a large number of institutions and scholars have been paying close attention to this field, providing new directions for exploring hazardous materials’ distribution patterns. This paper employs two fuzzy random variables, transportation cost and risk, to put forward a bi-level minimum objective programming model with a chance measure constraint within a specified chance level. The lower level is to seek minimum transportation costs and the upper level is for minimum risk. The model presented in this article simultaneously designs the hybrid algorithm, which is the combination of the fuzzy random simulation with the genetic algorithm. In the end, a small-scale instance is given to account for the efficiency of the presented model and algorithm, and the best distribution solution is presented