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A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints

Author

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  • Leung, Stephen C.H.
  • Zhang, Zhenzhen
  • Zhang, Defu
  • Hua, Xian
  • Lim, Ming K.

Abstract

The two-dimensional loading heterogeneous fleet vehicle routing problem (2L-HFVRP) is a variant of the classical vehicle routing problem in which customers are served by a heterogeneous fleet of vehicles. These vehicles have different capacities, fixed and variable operating costs, length and width in dimension, and two-dimensional loading constraints. The objective of this problem is to minimize transportation cost of designed routes, according to which vehicles are used, to satisfy the customer demand. In this study, we proposed a simulated annealing with heuristic local search (SA_HLS) to solve the problem and the search was then extended with a collection of packing heuristics to solve the loading constraints in 2L-HFVRP. To speed up the search process, a data structure was used to record the information related to loading feasibility. The effectiveness of SA_HLS was tested on benchmark instances derived from the two-dimensional loading vehicle routing problem (2L-CVRP). In addition, the performance of SA_HLS was also compared with three other 2L-CVRP models and four HFVRP methods found in the literature.

Suggested Citation

  • Leung, Stephen C.H. & Zhang, Zhenzhen & Zhang, Defu & Hua, Xian & Lim, Ming K., 2013. "A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 225(2), pages 199-210.
  • Handle: RePEc:eee:ejores:v:225:y:2013:i:2:p:199-210
    DOI: 10.1016/j.ejor.2012.09.023
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    References listed on IDEAS

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    1. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Christos T., 2009. "A Guided Tabu Search for the Vehicle Routing Problem with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 195(3), pages 729-743, June.
    2. Manuel Iori & Silvano Martello, 2010. "Routing problems with loading constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(1), pages 4-27, July.
    3. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    4. Tarantilis, C. D. & Kiranoudis, C. T. & Vassiliadis, V. S., 2004. "A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 152(1), pages 148-158, January.
    5. Fuellerer, Guenther & Doerner, Karl F. & Hartl, Richard F. & Iori, Manuel, 2010. "Metaheuristics for vehicle routing problems with three-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 201(3), pages 751-759, March.
    6. Manuel Iori & Silvano Martello, 2010. "Rejoinder on: Routing problems with loading constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(1), pages 41-42, July.
    7. Imran, Arif & Salhi, Said & Wassan, Niaz A., 2009. "A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 509-518, September.
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    Citations

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    Cited by:

    1. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.
    2. repec:spr:annopr:v:236:y:2016:i:2:d:10.1007_s10479-014-1551-4 is not listed on IDEAS
    3. Côté, J.F. & Guastaroba, G. & Speranza, M.G., 2017. "The value of integrating loading and routing," European Journal of Operational Research, Elsevier, vol. 257(1), pages 89-105.
    4. Zhang, Junlong & Lam, William H.K. & Chen, Bi Yu, 2016. "On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows," European Journal of Operational Research, Elsevier, vol. 249(1), pages 144-154.
    5. Wei, Lijun & Zhang, Zhenzhen & Zhang, Defu & Lim, Andrew, 2015. "A variable neighborhood search for the capacitated vehicle routing problem with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 243(3), pages 798-814.
    6. repec:spr:cejnor:v:26:y:2018:i:1:d:10.1007_s10100-017-0484-9 is not listed on IDEAS
    7. repec:eee:ejores:v:265:y:2018:i:3:p:843-859 is not listed on IDEAS
    8. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    9. repec:pal:jorsoc:v:68:y:2017:i:11:d:10.1057_s41274-016-0151-x is not listed on IDEAS
    10. repec:eee:ejores:v:262:y:2017:i:3:p:966-980 is not listed on IDEAS
    11. Männel, Dirk & Bortfeldt, Andreas, 2016. "A hybrid algorithm for the vehicle routing problem with pickup and delivery and three-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 254(3), pages 840-858.
    12. İlker Küçükoğlu & Nursel Öztürk, 0. "A hybrid meta-heuristic algorithm for vehicle routing and packing problem with cross-docking," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-17.
    13. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    14. Zhang, Zhenzhen & Wei, Lijun & Lim, Andrew, 2015. "An evolutionary local search for the capacitated vehicle routing problem minimizing fuel consumption under three-dimensional loading constraints," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 20-35.

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