Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach

Castro, Juan P.; Landa-Silva, Dario; Moreno P�rez, Jos� A.

Abstract

This paper investigates the ability of a discrete particle swarm optimization algorithm (DPSO) to evolve solutions from infeasibility to feasibility for the Vehicle Routing Problem with Time Windows (VRPTW). The proposed algorithm incorporates some principles from multi-objective optimization to allow particles to conduct a dynamic trade-off between objectives in order to reach feasibility. The main contribution of this paper is to demonstrate that without incorporating tailored heuristics or operators to tackle infeasibility, it is possible to evolve very poor infeasible route-plans to very good feasible ones using swarm intelligence. © 2009 Springer-Verlag Berlin Heidelberg.

Citation

Castro, J. P., Landa-Silva, D., & Moreno Pérez, J. A. (2009). Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2008) (103-114). Springer Verlag. https://doi.org/10.1007/978-3-642-03211-0_9

• Publication Date: Oct 20, 2009
• Deposit Date: Feb 10, 2020
• Publisher: Springer Verlag
• Pages: 103-114
• Series Title: Studies in Computational Intelligence
• Series Number: 236
• Book Title: Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)
• ISBN: 978-3-642-03210-3
• DOI: https://doi.org/10.1007/978-3-642-03211-0_9
• Public URL: https://nottingham-repository.worktribe.com/output/3088154
• Publisher URL: https://link.springer.com/chapter/10.1007%2F978-3-642-03211-0_9