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Nature Inspired Cooperative Strategies for Optimization (NICSO 2008) pp 103–114Cite as

Exploring Feasible and Infeasible Regions in the Vehicle Routing Problem with Time Windows Using a Multi-objective Particle Swarm Optimization Approach

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Part of the Studies in Computational Intelligence book series (SCI,volume 236)

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.

Keywords

  • Particle Swarm Optimization
  • PSO
  • Multi-Objective
  • Vehicle Routing Problem with Time Windows
  • VRPTW

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  • DOI: 10.1007/978-3-642-03211-0_9
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Author information

Authors and Affiliations

  1. Automated Scheduling, Optimisation and Planning Research Group (ASAP), University of Nottingham, (UK)

    Juan P. Castro & Dario Landa-Silva

  2. Group of Intelligent Computing, Dpto. de Estadística, I.O. y Computación, Escuela Técnica Superior de Ingeniería Informática, Universidad de La Laguna, (Spain)

    José A. Moreno Pérez

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  1. Juan P. Castro
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  2. Dario Landa-Silva
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  3. José A. Moreno Pérez
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Editor information

Editors and Affiliations

  1. School of Computer Sciences and Information Technology, University of Nottingham, Jubilee Campus, NG81BB, Nottingham, UK

    Natalio Krasnogor

  2. Universidad de La Laguna, Tenerife, Spain

    María Belén Melián-Batista

  3. DEIOC, Facultad de Matemáticas, Universidad de La Laguna, 38271, La Laguna, Tenerife, Spain

    José Andrés Moreno Pérez & J. Marcos Moreno-Vega & 

  4. Department of Computer Science and Artificial Intelligence, E.T.S.I Informática y de Telecomunicación, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain

    David Alejandro Pelta

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Castro, J.P., Landa-Silva, D., Pérez, J.A.M. (2009). Exploring Feasible and Infeasible Regions in the Vehicle Routing Problem with Time Windows Using a Multi-objective Particle Swarm Optimization Approach. In: Krasnogor, N., Melián-Batista, M.B., Pérez, J.A.M., Moreno-Vega, J.M., Pelta, D.A. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2008). Studies in Computational Intelligence, vol 236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03211-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-03211-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

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