Fuzzy GRASP with path relinking for the Risk-constrained Cash-in-Transit Vehicle Routing Problem

Abstract

This paper considers a special case of famous vehicle routing problem with additional risk constraints, called the Risk-constrained Cash-in-Transit Vehicle Routing Problem (RCTVRP). We propose a fuzzy GRASP (Greedy Randomized Adaptive Search Procedure) hybridized with path relinking (PR) methodology for solving the RCTVRP. Introduced PR structure, which can be used for other vehicle routing problems, is implemented. To make the algorithm's time complexity smaller, new data structure for the RCTVRP is incorporated. Proposed fuzzy GRASP with PR hybrid shows better computational performance compared to its non-fuzzy version. Furthermore, computational results on publicly available data sets indicate that proposed algorithm outperforms all existing methods from the literature for solving the RCTVRP.