Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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Heterogeneous Fleet Vehicle Routing Problem with Customer Restriction using Hybrid Particle Swarm Optimization

Hybrid-PSO 해법을 이용한 수요지 제한이 있는 다용량 차량경로문제

  • Lee, Sang-Heon (Department of Operations Research, Korea National Defense University) ;
  • Hwang, Sun-Ho (Department of Operations Research, Korea National Defense University)
  • 이상헌 (국방대학교 운영분석학과) ;
  • 황선호 (국방대학교 운영분석학과)
  • Received : 20080000
  • Accepted : 20080000
  • Published : 2009.06.30
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Abstract

The heterogeneous fleet vehicle routing problem(HVRP) is a variant of the classical vehicle routing problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs and variable costs. We propose a new conceptual HVRPCR(HVRP with customer restriction) model including additional customer restrictions in HVRP. In this paper, we develop hybrid particle swarm optimization(HPSO) algorithm with 2-opt and node exchange technique for HVRP. The solution representation is a n-dimensional particle for HVRP with N customers. The decoding method for this representation starts with the transformation of particle into a priority list of customer to enter route and limit of vehicle to serve each customer. The vehicle routes are then constructed based on the customer priority list and limit of vehicle to serve. The proposed algorithm is tested using 8 benchmark problems and it consistently produces high-quality solutions, including new best solutions. The numerical results show that the proposed algorithm is robust and efficient.

Keywords

References

  1. Imran, A., Salhi, S., and Wassan, N. A. (2009), A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem, European Journal of Operational Research, 197, 509-518 https://doi.org/10.1016/j.ejor.2008.07.022
  2. Clark, G. and Wright, J. (1964), Scheduling of vehicle from a central depot to a number of delivery points, Operations Research, 12, 568-581 https://doi.org/10.1287/opre.12.4.568
  3. Cho, H. S. and Lee, D. M. (2008), 2006 Traffic congestion costs : estimation and trend analysis, The Korea Transport Institute, 02
  4. Choi, E. and Tcha, D.-W. (2007), A column generation approach to the heterogeneous fleet vehicle routing problem, Computer and Operations Research, 34, 2080-2095 https://doi.org/10.1016/j.cor.2005.08.002
  5. Dueck, G. (1993), New optimization heuristics : the great deluge algorithm and the record-to-record travel, Journal of Computational Physics, 104, 86-92 https://doi.org/10.1006/jcph.1993.1010
  6. Eberhart, R. C. and Shi, Y. (2000), Comparing inertia weights and constriction factors in particle swarm optimization, Proceedings of the 2000 Congress on Evolutionary Computation, 84-88
  7. Gendreau, M., Laporte, G., Musaraganyi, C., and Taillard E. D. (1999), A tabu search heuristic for the heterogeneous fleet vehicle routing problem, Computer and Operations Research, 26, 1153-1173 https://doi.org/10.1016/S0305-0548(98)00100-2
  8. Glover, F. (1997), Tabu search and adaptive memory problem programming : advances, applications and challenges, Interfaces in comp. Sc. and Oper. Res, 1-76
  9. Golden, B., Assad, A., Levy, L., and Gheysens, F. G. (1984), The fleet size and mix vehicle routing problem, Computer and Operations Research, 11, 49-66 https://doi.org/10.1016/0305-0548(84)90007-8
  10. http://ina2.eivd.ch/collaberateurs/etd/problems.dir/vrp.dir/vrp.html
  11. Kennedy. J. and Eberhart. R. C. (1995), Particle swarm optimization, Proceedings of IEEE international Conference on Neural Networks, 1942-1948
  12. Kennedy. J. and Eberhart. R. C. (2001), Swarm intelligence, San Francisco : Morgan Kaufman Publishers
  13. Liu, F. H. and Shen, S. Y. (1999), The fleet size and mix vehicle routing problem with time windows, Journal of the Operational Research Society, 50, 721-732 https://doi.org/10.1057/palgrave.jors.2600763
  14. Ochi, L. S., Viana, D. S., Drummond, L. M., and Victor, A. O. (1998), A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet, Future Generation Computation System (FGCS), 14, 285-292 https://doi.org/10.1016/S0167-739X(98)00034-X
  15. Salhi, S., Rand, G. K. (1987), Improvements to vehicle routing heuristic, Journal of the Operational Research Society, 293-295
  16. Salhi, S., Rand, G. K. (1993), Incorporating vehicle routing into the vehicle fleet composition problem, European Journal of Operation Research, 66, 313-330 https://doi.org/10.1016/0377-2217(93)90220-H
  17. Taillard, E. D. (1999), A heuristic column generation method for heterogeneous fleet, Recherche operationnelle(RAIRO), 33, 1-14 https://doi.org/10.1051/ro:1999101