Hybrid genetic ant colony optimization algorithm for capacitated vehicle routing problem with fuzzy demand — A case study on garbage collection system

Abstract

The logistics distribution problem, which is typically represented as the capacitated vehicle routing problem (CVRP), is a very important issue in logistics. Thus, this paper considers the CVRP with fuzzy demand (CVRPFD). As an NP-hard problem, many researches in CVRP apply meta-heuristic method rather than exact method. A hybrid genetic algorithm (GA) and ant colony optimization (ACO) is proposed in this study. It combines advantages of GA, ACO and two local search methods, namely Prim's algorithm and 2-opt. Verification of the proposed method's performance is conducted on eight benchmark data sets in CVRP. The results show that the proposed GACO algorithm is competitive with other existing algorithms for solving CVRP. Furthermore, the proposed method is also applied to solve garbage collection system which is represented as CVRPFD. The results are also very promising.