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Fast Ejection Chain Algorithms for Vehicle Routing with Time Windows

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Hybrid Metaheuristics (HM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3636))

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Abstract

This paper introduces a new algorithm, based on the concept of ejection chains, to effectively target vehicle routing problems with time window constraints (VRPTW). Ejection chains create powerful compound moves within Local Search algorithms. Their potential to yield state of the art algorithms has been validated for the traveling salesman problem (TSP), for example. We show how ejection chains can be used to tackle the more general VRPTW as well. The yardstick behind ejection chain procedures is the underlying reference structure; it is used to coordinate the moves that are available for the Local Search algorithm via a given set of transition rules. Our main contribution is the introduction of a new reference structure, generalizing reference structures previously suggested for the TSP. The new reference structure, together with a set of simple transition rules, is tailored to handle the asymmetric aspects in a VRPTW. We use Tabu Search for the generation of the ejection chains, and on a higher algorithmic level, the ejection chain process is embedded into an Iterated Local Search algorithm. Computational results confirm that this approach leads to very fast algorithms, showing that ejection chain algorithms have the potential to compete with state of the art algorithms for the VRPTW.

This research was performed on behalf of the Centre for Quantitative Methods, CQM BV, P.O. Box 414, 5600 AK, Eindhoven, The Netherlands.

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References

  1. Aarts, E.H.L., Lenstra, J.K.: Local search in combinatorial optimization. Wiley, Chichester (1996)

    Google Scholar 

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

    Article  Google Scholar 

  3. Clark, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Operations Research 12, 568–581 (1964)

    Article  Google Scholar 

  4. den Besten, M., Stützle, T., Dorigo, M.: Design of iterated local search algorithms. In: Boers, E.J.W., Gottlieb, J., Lanzi, P.L., Smith, R.E., Cagnoni, S., Hart, E., Raidl, G.R., Tijink, H. (eds.) EvoIASP 2001, EvoWorkshops 2001, EvoFlight 2001, EvoSTIM 2001, EvoCOP 2001, and EvoLearn 2001. LNCS, vol. 2037, pp. 441–451. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  5. Gamboa, D., Rego, C., Glover, F.: Implementation analysis of efficient heuristic algorithms for the traveling salesman problem. Computers and Operations Research (2005) (to appear)

    Google Scholar 

  6. George, P.L., Borouchaki, H.: Delaunay Triangulation and Meshing, Applications to Finite Elements. Hermes (1998)

    Google Scholar 

  7. Glover, F.: Ejection chains, reference structures and alternating path methods for traveling salesman problems. Discrete Applied Mathematics 65, 223–253 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  8. Glover, F., Laguna, M.: Tabu Search. Kluwer, Dordrecht (1998)

    Google Scholar 

  9. Kilby, P., Prosser, P., Shaw, P.: Guided local search for the vehicle routing problem. In: Voss, S., Martello, S., Osman, I.H., Roucairol, C. (eds.) Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, pp. 473–486. Kluwer, Boston (1997)

    Google Scholar 

  10. Lin, S., Kernighan, B.W.: An effective heuristic for the traveling salesman problem. Operations Research 21, 498–516 (1973)

    Article  MATH  MathSciNet  Google Scholar 

  11. Lourenco, H.R., Martin, O., Stützle, T.: Iterated local search. In: Glover, F., Kochenberger, G. (eds.) The Handbook of Metaheuristics, pp. 321–353. Kluwer, Norwell (2002)

    Google Scholar 

  12. Martin, O.C., Otto, S.W.: Combining Simulated Annealing with Local Search Heuristics. Annals of Operations Research, vol. 63, pp. 57–75 (1996)

    Google Scholar 

  13. Rego, C.: A subpath ejection method for the vehicle routing problem. Management Science 44(10), 1447–1459 (1998)

    Article  MATH  Google Scholar 

  14. Rochat, Y., Taillard, É.D.: Probalistic diversification and intensification in local search for vehicle routing. Journal of Heuristics 1, 147–167 (1995)

    Article  MATH  Google Scholar 

  15. Solomon, M.: Algorithms for the vehicle routing and scheduling problem with time window constraints. Operations Research 35, 254–265 (1987)

    Article  MATH  MathSciNet  Google Scholar 

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

    Book  MATH  Google Scholar 

  17. Xu, J., Kelly, J.: A network-flow based tabu search heuristic for the vehicle routing problem. Transportation Science 30, 379–393 (1996)

    Article  MATH  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Sontrop, H., van der Horn, P., Uetz, M. (2005). Fast Ejection Chain Algorithms for Vehicle Routing with Time Windows. In: Blesa, M.J., Blum, C., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2005. Lecture Notes in Computer Science, vol 3636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546245_8

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  • DOI: https://doi.org/10.1007/11546245_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28535-9

  • Online ISBN: 978-3-540-31898-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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