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An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10142)

Abstract

An Australian company is faced with the logistics problem of distributing small quantities of fibre boards to hundreds of customers every day. The resulting Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints has to be solved within a single hour, hence the use of a heuristic instead of an exact method. In previous work, the loading was performed after optimising the routes, which in some cases generated infeasible solutions in need of a repair mechanism. In this work, the feasibility of the loading constraints is maintained during the route optimisation. Iterated Local Search has proved very effective at solving vehicle routing problems. Its success is mainly due to its biased sampling of locl optima. However, its performance heavily depends on the perturbation procedure. We trialled different perturbation procedures where the first one perturbs the given solution by moving deliveries that incur the highest cost on the objective function, whilst the second one moves deliveries that have been shifted less frequently by the local search in previous iterations. Our industry partner provided six sets of daily orders which have varied characteristics in terms of the number of customers, customer distribution, number of fibre boards and fibre boards’ sizes. Our investigations show that an instance becomes more constrained when the customer order contains many different board sizes, which makes it harder to find feasible solutions. The results show that the proposed perturbation procedures significantly enhances the performance of iterated local search specifically on such constrained problems.

Keywords

  • Iterated local search
  • Perturbation operator
  • Vehicle routing problem
  • Time windows
  • 3-Dimensional loading constraints

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References

  1. Avci, M., Topaloglu, S.: An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries. Comput. Ind. Eng. 83, 15–29 (2015)

    CrossRef  Google Scholar 

  2. Baker, B., Coffman Jr., E., Rivest, R.: Orthogonal packings in two dimensions. SIAM J. Comput. 9(4), 846–855 (1980)

    MathSciNet  CrossRef  MATH  Google Scholar 

  3. Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. (CSUR) 35(3), 268–308 (2003)

    CrossRef  Google Scholar 

  4. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, part i: route construction and local search algorithms. Transp. Sci. 39(1), 104–118 (2005)

    CrossRef  Google Scholar 

  5. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, part ii: metaheuristics. Transp. Sci. 39(1), 119–139 (2005)

    CrossRef  Google Scholar 

  6. Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res. 12(4), 568–581 (1964)

    CrossRef  Google Scholar 

  7. Cuervo, D.P., Goos, P., Sörensen, K., Arráiz, E.: An iterated local search algorithm for the vehicle routing problem with backhauls. Eur. J. Oper. Res. 237(2), 454–464 (2014)

    CrossRef  MATH  Google Scholar 

  8. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manag. Sci. 6(1), 80–91 (1959)

    MathSciNet  CrossRef  MATH  Google Scholar 

  9. Duhamel, C., Lacomme, P., Quilliot, A., Toussaint, H.: A multi-start evolutionary local search for the two-dimensional loading capacitated vehicle routing problem. Comput. Oper. Res. 38(3), 617–640 (2011)

    CrossRef  MATH  Google Scholar 

  10. Fuellerer, G., Doerner, K.F., Hartl, R.F., Iori, M.: Metaheuristics for vehicle routing problems with three-dimensional loading constraints. Eur. J. Oper. Res. 201(3), 751–759 (2010)

    CrossRef  MATH  Google Scholar 

  11. Gendreau, M., Iori, M., Laporte, G., Martello, S.: A tabu search algorithm for a routing and container loading problem. Transp. Sci. 40(3), 342–350 (2006)

    CrossRef  Google Scholar 

  12. Junqueira, L., Morabito, R.: Heuristic algorithms for a three-dimensional loading capacitated vehicle routing problem in a carrier. Comput. Ind. Eng. 88, 110–130 (2015)

    CrossRef  Google Scholar 

  13. Laporte, G.: The vehicle routing problem: an overview of exact and approximate algorithms. Eur. J. Oper. Res. 59(3), 345–358 (1992)

    CrossRef  MATH  Google Scholar 

  14. Lodi, A., Martello, S., Vigo, D.: Heuristic and metaheuristic approaches for a class of two-dimensional bin packing problems. INFORMS J. Comput. 11(4), 345–357 (1999)

    MathSciNet  CrossRef  MATH  Google Scholar 

  15. Lourenço, H.R., Martin, O.C., Stützle, T.: Iterated local search. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics, vol. 57, pp. 320–353. Springer, Boston (2003)

    CrossRef  Google Scholar 

  16. Moura, A., Oliveira, J.F.: An integrated approach to the vehicle routing and container loading problems. OR Spectr. 31(4), 775–800 (2009)

    MathSciNet  CrossRef  MATH  Google Scholar 

  17. Pace, S., Turky, A., Moser, I., Aleti, A.: Distributing fibre boards: a practical application of the heterogeneous fleet vehicle routing problem with time windows and three-dimensional loading constraints. Procedia Comput. Sci. 51, 2257–2266 (2015)

    CrossRef  Google Scholar 

  18. Pollaris, H., Braekers, K., Caris, A., Janssens, G.K., Limbourg, S.: Vehicle routing problems with loading constraints: state-of-the-art and future directions. OR Spectr. 37(2), 297–330 (2015)

    MathSciNet  CrossRef  MATH  Google Scholar 

  19. Reimann, M., Doerner, K., Hartl, R.F.: D-ants: savings based ants divide and conquer the vehicle routing problem. Comput. Oper. Res. 31(4), 563–591 (2004)

    CrossRef  MATH  Google Scholar 

  20. Silva, M.M., Subramanian, A., Ochi, L.S.: An iterated local search heuristic for the split delivery vehicle routing problem. Comput. Oper. Res. 53, 234–249 (2015)

    MathSciNet  CrossRef  MATH  Google Scholar 

  21. Tarantilis, C., Zachariadis, E., Kiranoudis, C.: A hybrid metaheuristic algorithm for the integrated vehicle routing and three-dimensional container-loading problem. IEEE Trans. Intell. Transp. Syst. 10(2), 255–271 (2009)

    CrossRef  Google Scholar 

  22. Toth, P., Vigo, D.: The Vehicle Routing Problem. Society for Industrial and Applied Mathematics (2002)

    Google Scholar 

  23. Tricoire, F., Doerner, K., Hartl, R., Iori, M.: Heuristic and exact algorithms for the multi-pile vehicle routing problem. OR Spectr. 33(4), 931–959 (2011)

    MathSciNet  CrossRef  MATH  Google Scholar 

  24. Wang, F., Tao, Y., Shi, N.: A survey on vehicle routing problem with loading constraints. In: International Joint Conference on Computational Sciences and Optimization, CSO 2009, vol. 2, pp. 602–606. IEEE (2009)

    Google Scholar 

  25. Wei, L., Zhang, Z., Lim, A.: An adaptive variable neighborhood search for a heterogeneous fleet vehicle routing problem with three-dimensional loading constraints. IEEE Comput. Intell. Mag. 9(4), 18–30 (2014)

    CrossRef  Google Scholar 

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Turky, A., Moser, I., Aleti, A. (2017). An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints. In: Wagner, M., Li, X., Hendtlass, T. (eds) Artificial Life and Computational Intelligence. ACALCI 2017. Lecture Notes in Computer Science(), vol 10142. Springer, Cham. https://doi.org/10.1007/978-3-319-51691-2_24

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  • DOI: https://doi.org/10.1007/978-3-319-51691-2_24

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