Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

Abstract

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.

Keywords:

• Hazardous materials transportation
• multi-objective programming
• fuzzy chance-constrained programming
• hybrid intelligent algorithm

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by grants from the National Science Fund for Distinguished Young Scholars [grant number 71025005]; the National Natural Science Foundation of China [grant number 71371027], [grant number 91224001]; Program for New Century Excellent Talents in University [grant number NCET-13-0649].