On solutions to capacitated vehicle routing problem using an enhanced ant colony optimization technique

Abstract

This paper presents an enhanced ant colony optimization (ACO) algorithm for solving the capacitated vehicle routing problem (CVRP). CVRP is the most elementary version of VRP, but also a difficult combinatorial problem which contains both the TSP (routing) and BPP (packing) problems as special cases. In the CVRP a number of vehicles having uniform capacity starts and terminates at a common depot, services a set of customers with certain demands at minimum transit cost. In this paper, an enhanced version of ACO algorithm is implemented on Fisher and Christofides benchmark problems. Computational results compared with the performance of different algorithms and relaxations are presented. These results indicate that the proposed algorithm is a comparative approach to solve CVRP. The article is concluded by examining the possible future research directions in this field.