A multi-valued discrete particle swarm optimization for the evacuation vehicle routing problem

  • Authors:
  • Marina Yusoff;Junaidah Ariffin;Azlinah Mohamed

  • Affiliations:
  • Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia;Flood-Marine Excellence Centre, Faculty of Civil Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia;Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

  • Venue:
  • ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
  • Year:
  • 2011
  • Discrete particle swarm optimization for solving a single to multiple destinations in evacuation planning

    MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control

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Abstract

An optimal evacuation route plan has to be established to overcome the problem of poor coordination and uneven distribution of vehicles before or during disaster. This article introduces the evacuation vehicle routing problem (EVRP) as a new variant to the vehicle routing problem (VRP). EVRP is a process of moving vehicles from a vehicle location to the potentially flooded area (PFA), and from PFA to relief center using a number of capacitated vehicles. This paper examines the application of a multi-valued discrete particle swarm optimization (DPSO) for routing of vehicles from vehicle location to PFA. A solution representation is adopted and modified from the solution of the shortest path problem (SPP) to accommodate this problem. Experimental results were tested based on the objective function of finding a minimum total travelling time using datasets from a flash flood evacuation operation. DPSO was found to yield better results than a genetic algorithm (GA).