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A Harmony Search Approach for the Selective Pick-Up and Delivery Problem with Delayed Drop-Off

  • Javier Del Ser
  • Miren Nekane Bilbao
  • Cristina Perfecto
  • Sancho Salcedo-Sanz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 382)

Abstract

In the last years freight transportation has undergone a sharp increase in the scales of its underlying processes and protocols mainly due to the ever-growing community of users and the increasing number of on-line shopping stores. Furthermore, when dealing with the last stage of the shipping chain an additional component of complexity enters the picture as a result of the fixed availability of the destination of the good to be delivered. As such, business opening hours and daily work schedules often clash with the delivery times programmed by couriers along their routes. In case of conflict, the courier must come to an arrangement with the destination of the package to be delivered or, alternatively, drop it off at a local depot to let the destination pick it up at his/her time convenience. In this context this paper will formulate a variant of the so-called courier problem under economic profitability criteria including the cost penalty derived from the delayed drop-off. In this context, if the courier delivers the package to its intended destination before its associated deadline, he is paid a reward. However, if he misses to deliver in time, the courier may still deliver it at the destination depending on its availability or, alternatively, drop it off at the local depot assuming a certain cost. The manuscript will formulate the mathematical optimization problem that models this logistics process and solve it efficiently by means of the Harmony Search algorithm. A simulation benchmark will be discussed to validate the solutions provided by this meta-heuristic solver and to compare its performance to other algorithmic counterparts.

Keywords

Courier problem Delayed drop-off Hill climbing Genetic algorithm Harmony search 

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References

  1. 1.
    Jones Lang Lasalle IP, Inc.: E-commerce boom triggers transformation in retail logistics. White paper (2013)Google Scholar
  2. 2.
    eMarketer: Worldwide B2C Ecommerce: Q3 2014 Complete Forecast. Research report (2014)Google Scholar
  3. 3.
    Dror, M., Trudeau, G.: Savings by Split Delivery Routing. Transportation Science 23, 141–145 (1989)zbMATHMathSciNetCrossRefGoogle Scholar
  4. 4.
    Archetti, C., Speranza, M.G., Hertz, A.: A Tabu Search Algorithm for the Split Delivery Vehicle Routing Problem. Transportation Science 40(1), 64–73 (2006)CrossRefGoogle Scholar
  5. 5.
    Ho, S.C., Haugland, D.: A Tabu Search Heuristic for the Vehicle Routing Problem with Time Windows and Split Deliveries. Computers and Operations Research 31(12), 1947–1964 (2004)zbMATHCrossRefGoogle Scholar
  6. 6.
    Lin, Y.H., Batta, R., Rogerson, P.A., Blatt, A., Flanigan, M.: A Logistics Model for Delivery of Prioritized Items: Application to a Disaster Relief Effort. Technical report. New York: University of Buffalo (2009)Google Scholar
  7. 7.
    Balcik, B., Beamon, B.M., Smilowitz, K.: Last Mile Distribution in Humanitarian Relief. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations 12(2), 51–63 (2008)CrossRefGoogle Scholar
  8. 8.
    Mester, D., Bräysy, O., Dullaert, W.: A Multi-Parametric Evolution Strategies Algorithm for Vehicle Routing Problems. Expert Systems with Applications 32, 508–517 (2007)CrossRefGoogle Scholar
  9. 9.
    Alba, E., Dorronsoro, B.: Computing Nine New Best-so-far Solutions for Capacitated VRP with a Cellular Genetic Algorithm. Information Processing Letters 98, 225–230 (2006)zbMATHMathSciNetCrossRefGoogle Scholar
  10. 10.
    Doerner, K.F., Hartl, R.F., Lucka, M.: A Parallel Version of the D-ant Algorithm for the Vehicle Routing Problem. Parallel Numerics, 109–118 (2005)Google Scholar
  11. 11.
    Li, X., Tian, P.: An ant colony system for the open vehicle routing problem. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 356–363. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  12. 12.
    Layeb, A., Ammi, M., Chikhi, S.: A GRASP Algorithm Based on New Randomized Heuristic for Vehicle Routing Problem. Journal of Computing and Information Technology 1, 35–46 (2013)CrossRefGoogle Scholar
  13. 13.
    Suárez, J.G., Anticona, M.T.: Solving the capacitated vehicle routing problem and the split delivery using GRASP metaheuristic. In: Bramer, M. (ed.) IFIP AI 2010. IFIP AICT, vol. 331, pp. 243–249. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  14. 14.
    Chaovalitwongse, W., Kim, D., Pardalos, P.M.: GRASP with a New Local Search Scheme for Vehicle Routing Problems with Time Windows. Journal of Combinatorial Optimization 7, 179–207 (2003)zbMATHMathSciNetCrossRefGoogle Scholar
  15. 15.
    Wang, C., Zhao, F., Mu, D., Sutherland, J.W.: Simulated annealing for a vehicle routing problem with simultaneous pickup-delivery and time windows. In: Prabhu, V., Taisch, M., Kiritsis, D. (eds.) APMS 2013, Part II. IFIP AICT, vol. 415, pp. 170–177. Springer, Heidelberg (2013) Google Scholar
  16. 16.
    Chen, S., Golden, B., Wasil, E.: The Split Delivery Vehicle Routing Problem: Applications, Algorithms, Test Problems, and Computational Results. Networks 49, 318–329 (2007)zbMATHMathSciNetCrossRefGoogle Scholar
  17. 17.
    Czech, Z.J., Czarnas, P.: Parallel Simulated Annealing for the Vehicle Routing Problem with Time Windows. In: Euromicro Workshop on Parallel, Distributed and Network-based Processing, pp. 376–383 (2002)Google Scholar
  18. 18.
    Pirkwieser, S., Raidl, G.R.: Multilevel variable neighborhood search for periodic routing problems. In: Cowling, P., Merz, P. (eds.) EvoCOP 2010. LNCS, vol. 6022, pp. 226–238. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  19. 19.
    Kytöjoki, J., Nuortio, T., Bräysy, O., Gendreau, M.: An Efficient Variable Neighborhood Search Heuristic for Very Large Scale Vehicle Routing Problems. Computers & Operations Research 34, 2743–2757 (2007)zbMATHCrossRefGoogle Scholar
  20. 20.
    Gendreau, M., Potvin, J.-Y., Bräumlaysy, O., Hasle, G., Løkketangen, A.: Metaheuristics for the Vehicle Routing Problem and Its Extensions: A Categorized Bibliography. Operations Research/Computer Science Interfaces 43, 143–169 (2008)CrossRefGoogle Scholar
  21. 21.
    Geem, Z.W., Kim, J.H., Loganathan, G.V.: A New Heuristic Optimization Algorithm: Harmony Search. Simulation 76(2), 60–68 (2001)CrossRefGoogle Scholar
  22. 22.
    Manjarres, D., Landa-Torres, I., Gil-Lopez, S., Del Ser, J., Bilbao, M.N., Salcedo-Sanz, S., Geem, Z.W.: A Survey on Applications of the Harmony Search Algorithm. Engineering Applications of Artificial Intelligence 26(8), 1818–1831 (2013)CrossRefGoogle Scholar
  23. 23.
    Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Upper Saddle River. Prentice Hall (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Javier Del Ser
    • 1
  • Miren Nekane Bilbao
    • 2
  • Cristina Perfecto
    • 2
  • Sancho Salcedo-Sanz
    • 3
  1. 1.TECNALIA. OPTIMA UnitDerioSpain
  2. 2.University of the Basque Country UPV/EHUBilbaoSpain
  3. 3.Universidad de AlcaláAlcalá de HenaresSpain

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