Modified Discrete Glowworm Swarm Optimization Algorithm Based on Time Window Division for Multi-objective VRPTW

Modified Discrete Glowworm Swarm Optimization Algorithm Based on Time Window Division for Multi-objective VRPTW

A modified discrete glowworm swarm optimization algorithm based on time window division (MDGSOTWD) is proposed to solve multi-objective vehicle routing problems with time windows (MVRPTW), which is a well-known NP-hard combinatorial optimization problem. In MDGSO-TWD, customers are divided into different classes according to their time windows so as to reduce the population generation time and neighborhood search time; the accuracy of solutions is enhanced by introducing memetic local search and several improvement measures of standard GSO; a new Pareto technique is designed to screen out excellent individuals. Parameter setting of MDGSO-TWD is discussed to enhance the algorithm performance. The feasibility and effectiveness of MDGSO-TWD is verified by analyzing the improvement strategies and comparing with standard GSO. Furthermore, the superiority of MDGSO-TWD is hightlighted by comparing with the state-of-the-art algorithms and the best results reported in the literature. Experimental results show that the proposed algorithm is competitive for MVRPTW in terms of the quality of solutions and the computing time.