A lexicographic approach for the bi-objective selective pickup and delivery problem with time windows and paired demands

OR in Transportation
  • 155 Downloads

Abstract

In pickup and delivery problems (PDPs), the aim is to transport loads from pickup locations (suppliers) to delivery locations (customers) using a set of vehicles while respecting a set of constraints. In this paper, we discuss a new variant of the PDP which has not been treated yet in the literature to our best knowledge. This new variant is the selective pickup and delivery problem with time windows and paired demands (SPDPTWPD). Its first specificity relies on the occurrence of time Windows, capacity and precedence constraints. In addition, it includes several depots and a fleet of vehicles, and the selective aspect must be taken into account. It means the choice of customers to be served when the global capacity of the vehicles is not sufficient. We proposed firstly a new mono-objective model to solve the SPDPTWPD. Then we tested our proposed algorithm on benchmark instances of near (less constrained) problems from the literature. Secondly, we have generated new instances adapted to the considered problem. Thirdly, we worked on a lexicographic approach to deal with the multi-objective aspect of our problem. The efficiency of our approaches is shown by the obtained results.

Keywords

Transportation Routing problems City logistics Exact algorithms 

Notes

Acknowledgements

This work is supported by the ANR (French National Research Agency) in the framework of the project TCDU (Collaborative Transportation in Urban Distribution). This project ANR-14-CE22-0017 is labelled by the Pôle Véhicule du Futur, and is jointly performed by four partners, the three french universities of technology (UTT, UTBM, UTC) and the society Share And Move Solutions.

References

  1. Al Chami, Z., Manier, H., Manier, MA. (2016). New model for a variant of pick up and delivery problem. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, pp 1708–1713.Google Scholar
  2. Baldacci, R., Bartolini, E., & Mingozzi, A. (2011). An exact algorithm for the pickup and delivery problem with time windows. Operations Research, 59(2), 414–426.CrossRefGoogle Scholar
  3. Bent, R., & Van Hentenryck, P. (2006). A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows. Computers & Operations Research, 33(4), 875–893.CrossRefGoogle Scholar
  4. Collette, Y., & Siarry, P. (2013). Multiobjective optimization: Principles and case studies. Berlin: Springer.Google Scholar
  5. Cordeau, J. F., & Laporte, G. (2007). The dial-a-ride problem: Models and algorithms. Annals of Operations Research, 153(1), 29–46.CrossRefGoogle Scholar
  6. Cordeau, J. F., Laporte, G., Savelsbergh, M. W., & Vigo, D. (2006). Vehicle routing. Transportation, Handbooks in Operations Research and Management Science, 14, 367–428.CrossRefGoogle Scholar
  7. Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management science, 6(1), 80–91.CrossRefGoogle Scholar
  8. Desrosiers, J., Dumas, Y., & Soumis, F. (1986). A dynamic programming solution of the large-scale single-vehicle dial-a-ride problem with time windows. American Journal of Mathematical and Management Sciences, 6(3–4), 301–325.CrossRefGoogle Scholar
  9. Desrosiers, J., Dumas, Y., Solomon, M. M., & Soumis, F. (1995). Time constrained routing and scheduling. Handbooks in Operations Research and Management Science, 8, 35–139.CrossRefGoogle Scholar
  10. Dridi, IH., Kammarti, R., Borne, P., Ksouri, M. (2008). Un algorithme génétique pour le problème de ramassage et de livraison avec fenêtres de temps à plusieurs véhicules. In: CIFA 2008, Bucarest (Roumanie), Septembre 2008 Proc. Article 176.Google Scholar
  11. El-Hajj, R. (2015). Vehicle routing problems with profits, exact and heuristic approaches. PhD thesis, Compiègne.Google Scholar
  12. Furtadoa, M. G. S., Munaria, P., & Morabitoa, R. (2015). Pickup and delivery problem with time windows: a new compact two-index formulation. Tech. rep.: Federal University of São Carlos.Google Scholar
  13. Golden, B. L., Raghavan, S., & Wasil, E. A. (2008). The vehicle routing problem: latest advances and new challenges (Vol. 43). Berlin: Springer.CrossRefGoogle Scholar
  14. Hayari, N., Manier, M., Bloch, C., El Moudni, A. (2003). Un algorithme évolutionniste pour le problème de tournées sélectives avec contraintes de fenêtres de temps. In: 4ème Conférence Francophone de MOdélisation et SIMulation MOSIM, vol 3.Google Scholar
  15. Jih, W. R., & Hsu, J Yj. (1999). Dynamic vehicle routing using hybrid genetic algorithms. IEEE International Conference on Robotics and Automation, IEEE, 1, 453–458.Google Scholar
  16. Laporte, G. (2009). Fifty years of vehicle routing. Transportation Science, 43(4), 408–416.CrossRefGoogle Scholar
  17. Laporte, G., & Osman, I. H. (1995). Routing problems: A bibliography. Annals of Operations Research, 61(1), 227–262.CrossRefGoogle Scholar
  18. Lenstra, J. K., & Kan, A. (1981). Complexity of vehicle routing and scheduling problems. Networks, 11(2), 221–227.CrossRefGoogle Scholar
  19. Li, H., & Lim, A. (2003). A metaheuristic for the pickup and delivery problem with time windows. International Journal on Artificial Intelligence Tools, 12(02), 173–186.CrossRefGoogle Scholar
  20. Lim, H., Lim, A., Rodrigues, B. (2002). Solving the pickup and delivery problem with time windows using squeaky wheel optimization with local search. In: Proceedings of AMCIS 2002, p 319.Google Scholar
  21. Lu, Q., & Dessouky, M. M. (2006). A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows. European Journal of Operational Research, 175(2), 672–687.CrossRefGoogle Scholar
  22. Nalepa, J., Blocho, M. (2016). Enhanced guided ejection search for the pickup and delivery problem with time windows. In: Asian Conference on Intelligent Information and Database Systems, Springer, pp 388–398.Google Scholar
  23. Nanry, W. P., & Barnes, J. W. (2000). Solving the pickup and delivery problem with time windows using reactive tabu search. Transportation Research Part B: Methodological, 34(2), 107–121.CrossRefGoogle Scholar
  24. Nguyen, PK., Crainic, TG., Toulouse, M. (2015). Multi-trip pickup and delivery problem with time windows and synchronization. Annals of Operations Research, 1–36. doi: 10.1007/s10479-015-2001-7.
  25. Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008). A survey on pickup and delivery problems. part i: Transportation between customers and depot. Journal für Betriebswirtschaft, 58(1), 21–51.CrossRefGoogle Scholar
  26. Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008). A survey on pickup and delivery problems. part ii: Transportation between pickup and delivery locations. Journal für Betriebswirtschaft, 58(2), 81–117.CrossRefGoogle Scholar
  27. Psaraftis, H. N. (1983). An exact algorithm for the single vehicle many-to-many dial-a-ride problem with time windows. Transportation Science, 17(3), 351–357.CrossRefGoogle Scholar
  28. Ropke, S., & Cordeau, J. F. (2009). Branch and cut and price for the pickup and delivery problem with time windows. Transportation Science, 43(3), 267–286.CrossRefGoogle Scholar
  29. Savelsbergh, M., & Sol, M. (1994). A branch-and-price algorithm for the pickup and delivery problem with time windows. Tech. rep., Technical Report COC-94-06, Georgia Institute of Technology, Atlanta.Google Scholar
  30. Savelsbergh, M. W., & Sol, M. (1995). The general pickup and delivery problem. Transportation science, 29(1), 17–29.CrossRefGoogle Scholar
  31. Schönberger, J., & Kopfer, H. (2005). Planning the incorporation of logistics service providers to fulfill precedence-and time window-constrained transport requests in a most profitable way. In B. Fleischmann & A. Klose (Eds.), Distribution Logistics. Lecture Notes in Economics and Mathematical Systems (Vol. 544). Berlin, Heidelberg: Springer.Google Scholar
  32. Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2), 254–265.CrossRefGoogle Scholar
  33. Ting, C. K., & Liao, X. L. (2013). The selective pickup and delivery problem: Formulation and a memetic algorithm. International Journal of Production Economics, 141(1), 199–211.CrossRefGoogle Scholar
  34. Toth, P., Vigo, D. (2002). The vehicle routing problem (society for industrial and applied mathematics, philadelphia). Tech. rep., ISBN 0-89871-579-2.Google Scholar
  35. Toth, P., & Vigo, D. (2014). Vehicle routing: Problems, methods, and applications (Vol. 18). Philadelphia: Society for Industrial and Applied Mathematics.CrossRefGoogle Scholar
  36. Velasco, N., Dejax, P., Gueret, C. (2006). Un algorithme génétique pour un problème de collectes et livraisons bi-objectif. In: 6ème Conférence Francophone de MOdélisation et SIMulation MOSIM, Rabat, Morocco.Google Scholar
  37. Wang, C., Mu, D., Zhao, F., & Sutherland, J. W. (2015). A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup-delivery and time windows. Computers & Industrial Engineering, 83, 111–122.CrossRefGoogle Scholar
  38. Yao, B., Yu, B., Hu, P., Gao, J., & Zhang, M. (2016). An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot. Annals of Operations Research, 242(2), 303–320.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.UTBM, OPERAUniv. Bourgogne Franche -ComtéBelfortFrance

Personalised recommendations