The Effect of Cooperation in Pickup and Multiple Delivery Problems

Philip Mourdjis, Fiona Polack, Peter Cowling, Yujie Chen, Martin Robinson

Abstract

Small logistics companies operate in many towns and cities across the UK, and need to be able to compete with larger delivery companies who can leverage economies of scale to provide lower costs to customers. If small companies were willing to work together, all could benefit from reduced operating costs, enabling them to compete and survive against larger delivery companies. In cooperation with Transfaction Ltd., we investigate dynamic scheduling of shared loads for real-world, long distance truck haulage in the UK. We model the problem as a dynamic pickup and multiple delivery problem (PMDP). The PMDP is a one-many problem (one pickup, many drop-offs), unlike the more widely researched one-one (pickup and delivery problem, PDP) and one-many-one (vehicle routing problem, VRP) problems.

References

  1. Albareda-Sambola, M., Fernández, E., and Laporte, G. (2014). The dynamic multiperiod vehicle routing problem with probabilistic information. Computers & Operations Research, 48(1):31-39.
  2. Belhaiza, S., Hansen, P., and Laporte, G. (2013). A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows. Computers & Operations Research, 52 part B:269-281.
  3. Benavent, E., Landete, M., Mota, E., and Tirado, G. (2015). The multiple vehicle pickup and delivery problem with LIFO constraints. European Journal of Operational Research, 243(3):752-762.
  4. Berbeglia, G., Cordeau, J.-F., Gribkovskaia, I., and Laporte, G. (2007). Static pickup and delivery problems: a classification scheme and survey. Top, 15(1):1-31.
  5. Berbeglia, G., Cordeau, J.-F., and Laporte, G. (2010). Dynamic pickup and delivery problems. European Journal of Operational Research, 202(1):8-15.
  6. Bräysy, O. (2003). A reactive variable neighborhood search for the vehicle-routing problem with time windows. INFORMS Journal on Computing, 15(4):347-368.
  7. Bräysy, O. and Gendreau, M. (2005a). Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms. Transportation Science, 39(1):104-118.
  8. Bräysy, O. and Gendreau, M. (2005b). Vehicle Routing Problem with Time Windows, Part II: Metaheuristics. Transportation Science, 39(1):119-139.
  9. Cherkesly, M., Desaulniers, G., and Laporte, G. (2015). Branch-Price-and-Cut Algorithns for the Pickup and Delivery Problem with Time Windows and LIFO Loading. Computers & Operations Research, 62(1):23-35.
  10. Clarke, G. and Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4):568-581.
  11. Crainic, T. G., Nguyen, P. K., and Toulouse, M. (2015). Synchronized Multi-Trip Multi-Traffic Pickup & Delivery in City Logistics. CIRRELT, 05(February):1- 24.
  12. Demir, E., Bekta, T., and Laporte, G. (2014). A review of recent research on green road freight transportation. European Journal of Operational Research, 237(3):775-793.
  13. Desaulniers, G., Desrosiers, J., Solomon, M. M., Erdmann, A., and Soumis, F. (2002). VRP with pickup and delivery. In Toth, P. and Vigo, D., editors, The vehicle routing problem, pages 225-242. SIAM.
  14. Dff International Ltd, R. (2014). RHA Cost Tables. Retrieved from http://www.rha.uk.net/.
  15. Dff International Ltd, R. (2015). RHA National Directory of Hauliers. Retrieved from http://www.rha.uk.net/.
  16. Dumas, Y., Desrosiers, J., and Soumis, F. (1991). The pickup and delivery problem with time windows. European Journal of Operational Research, 54(1):7-22.
  17. Gendreau, M., Guertin, F., Potvin, J.-Y., and Séguin, R. (2006). Neighborhood Search Heuristics for a Dynamic Vehicle Dispatching Problem with Pick-ups and Deliveries. Transportation Research Part C: Emerging Technologies, 14(3):157-174.
  18. Gendreau, M., Hertz, A., and Laporte, G. (1992). New Insertion and Post Optimization Procedures for the Traveling Salesman Problem. Operations Research, 40(6):1086-1095.
  19. Gschwind, T., Irnich, S., and Mainz, D. (2012). Effective Handling of Dynamic Time Windows and Synchronization with Precedences for Exact Vehicle Routing. Technical report, Johannes Gutenberg University Mainz, Mainz, Germany. Retrieved from http://logistik.bwl.uni-mainz.de/.
  20. Laporte, G. (2009). Fifty years of vehicle routing. Transportation Science, 43(4):408-416.
  21. McLeod, F., Cherrett, T., Shingleton, D., Bekta, T., Speed, C., Davies, N., Dickinson, J., and Norgate, S. (2012). 'Sixth Sense Logistics: Challenges in supporting more flexible, human-centric scheduling in the service sector. In Annual Logistics Research Network (LRN) Conference, Cranfield, UK.
  22. Mitrovic-Minic, S., Krishnamurti, R., and Laporte, G. (2004). Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows. Transportation Research Part B: Methodological, 38(8):669-685.
  23. Mourdjis, P. J., Cowling, P. I., and Robinson, M. (2014). Metaheuristics for the pick-up and delivery problem with contracted orders. In Blum, C. and Ochoa, G., editors, Evolutionary Computation in Combinatorial Optimization, pages 170-181, Berlin Heidelberg. Springer-Verlag.
  24. Nahum, O. E. (2013). The Real-Time Multi-Objective Vehicle Routing Problem. Phd, Bar-Ilan University.
  25. Rochat, Y. and Taillard, Ó. D. (1995). Probabilistic diversification and intensification in local search for vehicle routing. Journal of heuristics, 1(1):147-167.
  26. Savelsbergh, M. W. P. (1992). The Vehicle Routing Problem with Time Windows: Minimizing Route Duration. INFORMS Journal on Computing, 4(2):146-154.
  27. Taillard, Ó. D., Badeau, P., Gendreau, M., Guertin, F., and Potvin, J.-Y. (1997). A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows. Transportation Science, 31(2):170-186.
  28. Toth, P. and Vigo, D. (1997). Heuristic algorithms for the handicapped persons transportation problem. Transportation Science, 31(1):60-71.
  29. Xu, H., Chen, Z.-L., Rajagopal, S., and Arunapuram, S. (2003). Solving a Practical Pickup and Delivery Problem. Transportation Science, 37(3):347-364.
Download


Paper Citation


in Harvard Style

Mourdjis P., Polack F., Cowling P., Chen Y. and Robinson M. (2016). The Effect of Cooperation in Pickup and Multiple Delivery Problems . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 287-295. DOI: 10.5220/0005748902870295


in Bibtex Style

@conference{icores16,
author={Philip Mourdjis and Fiona Polack and Peter Cowling and Yujie Chen and Martin Robinson},
title={The Effect of Cooperation in Pickup and Multiple Delivery Problems},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2016},
pages={287-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005748902870295},
isbn={978-989-758-171-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - The Effect of Cooperation in Pickup and Multiple Delivery Problems
SN - 978-989-758-171-7
AU - Mourdjis P.
AU - Polack F.
AU - Cowling P.
AU - Chen Y.
AU - Robinson M.
PY - 2016
SP - 287
EP - 295
DO - 10.5220/0005748902870295