A chance constrained programming approach for HazMat capacitated vehicle routing problem in Type-2 fuzzy environment

Abstract

Abstract This work focuses on a HazMat capacitated vehicle routing problem (H-CVRP) in type-2 fuzzy environment, which aims to determine a set of routes with the minimum transportation risk. Since uncertainty can lead to significant differences in transportation risk, we propose a H-CVRP model with the objective function involving trapezoidal interval type-2 fuzzy variables (IT2-FVs). Based on the credibility measure, a chance constrained programming (CCP) approach is employed to transform the H-CVRP model into its equivalent deterministic form. A simulated annealing algorithm (SAA) is designed to solve the equivalent deterministic model. The proposed SAA is a global optimization algorithm, which converges to the optimal solution with probability and has high parallelism. To test the performance of the proposed algorithm, the optimal solutions obtained by SAA are compared with the counterparts obtained by genetic algorithm (GA) and tabu search (TS). Experimental results indicate that the proposed SAA is competitive in terms of stability and efficiency. At last, a sensitivity analysis is presented to demonstrate the applicability of the proposed method.