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A Decentralized Coordination Algorithm for a Highly Dynamic Vehicle Routing Problem

동적 차량경로 문제에 대한 분산 알고리즘

  • Received : 2019.10.23
  • Accepted : 2019.11.28
  • Published : 2019.12.31

Abstract

The Dynamic Vehicle Routing Problem (DVRP) involves a combinatorial optimization problem where new customer demands become known over time, and old routes must be reconfigured to generate new routes while executing the current solution. We consider the high level of dynamism problem. An application of highly dynamic DVRP is the ambulance service where a patient contacts the service center, followed by an evaluation of case severity, and a visit by a practitioner/ ambulance is scheduled accordingly. This paper considers a variant of the DVRP and proposes a decentralized algorithm in which collaborators (Depot and Vehicle), both have only partial information about the entire system. The DVRP is modeled as a periodic re optimization of VRP using the proposed decentralized algorithm where collaborators exchange local information to achieve the best global objective for the current state of the system. We assume the existence of a dispatcher e.g., headquarter of the company who can communicate to vehicles in order to gather information and assigns the new visits to them. The effectiveness of the proposed decentralized coordination algorithm is further evaluated using benchmark data given in literature. The results show that the proposed method performed better than the compared algorithms which utilize the centralized coordination in 12 out of 21 benchmark problems.

Keywords

References

  1. Azi, N., Gendreau, M., and Potvin, J.Y., A dynamic vehicle routing problem with multiple delivery routes, Annals of Operations Research, 2012, Vol. 199, No. 1, pp. 103-112. https://doi.org/10.1007/s10479-011-0991-3
  2. Barkaoui, M. and Gendreau, M., An adaptive evolutionary approach for real-time vehicle routing and dispatching, Computers and Operations Research, 2013, Vol. 40, No. 7, pp. 1766-1776. https://doi.org/10.1016/j.cor.2013.01.022
  3. Beaudry, A., Laporte, G., Melo, T., and Nickel, S., Dynamic transportation of patients in hospitals, OR Spectrum, 2010, Vol. 32, No. 1, pp. 77-107. https://doi.org/10.1007/s00291-008-0135-6
  4. Bent, R.W. and Van Hentenryck, P., Scenario-based planning for partially dynamic vehicle routing with stochastic customers, Operations Research, 2004, Vol. 52, No. 6, pp. 977-987. https://doi.org/10.1287/opre.1040.0124
  5. Chen, Z.-L. and Xu, H., Dynamic column generation for dynamic vehicle routing with time windows, Transportation Science, 2006, Vol. 40, No. 1, pp. 74-88. https://doi.org/10.1287/trsc.1050.0133
  6. Christofides, N. and Beasley, J.E., The period routing problem, Networks, 1984, Vol. 14, No. 2, pp. 237-256. https://doi.org/10.1002/net.3230140205
  7. Coslovich, L., Pesenti, R., and Ukovich, W., A twophase insertion technique of unexpected customers for a dynamic dial-a-ride problem, European Journal of Operational Research, 2006, Vol. 175, No. 3, pp. 1605-1615. https://doi.org/10.1016/j.ejor.2005.02.038
  8. Dan, B., Zhu, W., Li, H., Sang, Y., and Liu, Y., Dynamic optimization model and algorithm design for emergency materials dispatch, Mathematical Problems in Engineering, 2013.
  9. Demirtas, Y.E., Ozdemir, E., and Demirtas, U., A particle swarm optimization for the dynamic vehicle routing problem, In Modeling, Simulation, and Applied Optimization (ICMSAO), 2015 6th International Conference on IEEE, 2015, pp. 1-5.
  10. Elhassania, M.J., Jaouad, B., and Ahmed, E.A., A New Hybrid Algorithm to Solve the Vehicle Routing Problem in the Dynamic Environment, International Journal of Soft Computing, 2013, Vol. 8, pp. 327-334.
  11. Euchi, J., Yassine, A., and Chabchoub, H., The dynamic vehicle routing problem : Solution with hybrid metaheuristic approach, Swarm and Evolutionary Computation, 2015, Vol. 21, pp. 41-53. https://doi.org/10.1016/j.swevo.2014.12.003
  12. Fisher, M.L. and Jaikumar, R., A generalized assignment heuristic for vehicle routing, Networks, 1981, Vol. 11, No. 2, pp. 109-124. https://doi.org/10.1002/net.3230110205
  13. Gendreau, M., Guertin, F., Potvin, J.-Y., and Seguin, R., Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries, Transportation Research Part C : Emerging Technologies, 2006, Vol. 14, No. 3, pp. 157-174. https://doi.org/10.1016/j.trc.2006.03.002
  14. Gendreau, M., Guertin, F., Potvin, J.-Y., and Taillard, E., Parallel tabu search for real-time vehicle routing and dispatching, Transportation Science, 1999, Vol. 33, No. 4, pp. 381-390. https://doi.org/10.1287/trsc.33.4.381
  15. Hanshar, F.T. and Ombuki-Berman, B.M., Dynamic vehicle routing using genetic algorithms, Applied Intelligence, 2007, Vol. 27, pp. 89-99. https://doi.org/10.1007/s10489-006-0033-z
  16. Ichoua, S., Gendreau, M., and Potvin, J.-Y., Diversion issues in real-time vehicle dispatching, Transportation Science, 2000, Vol. 34, No. 4, pp. 426-438. https://doi.org/10.1287/trsc.34.4.426.12325
  17. Ichoua, S., Gendreau, M., and Potvin, J.Y., Exploiting knowledge about future demands for real-time vehicle dispatching, Transportation Science, 2006, Vol. 40, No. 2, pp. 211-225. https://doi.org/10.1287/trsc.1050.0114
  18. Ichoua, S., Gendreau, M., and Potvin, J.-Y., Vehicle dispatching with time-dependent travel times, European Journal of Operational Research, 2003, Vol. 144, No. 2, pp. 379-396. https://doi.org/10.1016/S0377-2217(02)00147-9
  19. Kergosien, Y., Lente, C., Piton, D., and Billaut, J.C., A tabu search heuristic for the dynamic transportation of patients between care units, European Journal of Operational Research, 2011, Vol. 214, No. 2, pp. 442-452. https://doi.org/10.1016/j.ejor.2011.04.033
  20. Khouadjia, M.R., Sarasola, B., Alba, E., Jourdan, L., and Talbi, E.G., A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests, Applied Soft Computing, 2012, Vol. 12, No. 4, pp. 1426-1439. https://doi.org/10.1016/j.asoc.2011.10.023
  21. Kilby, P., Professor, P.. and Shaw, P., Dynamic VRPs : a study of scenarios, Technical report APES-0-1998, University of Strathclyde, 1998.
  22. Larsen, A., Madsen, O., and Solomon, M., Partially Dynamic Vehicle Routing-Models and Algorithms, The Journal of the Operational Research Society, 2002, Vol. 53, No. 6. pp. 637-646. https://doi.org/10.1057/palgrave.jors.2601352
  23. Montemanni, R., Gambardella, L.M., Rizzoli, A.E., and Donati, A.V., Ant colony system for dynamic vehicle routing problem, Journal of Combinatorial Optimization, 2005, Vol. 10, pp. 327-343. https://doi.org/10.1007/s10878-005-4922-6
  24. Pillac, V., Gendreau, M., Gueret, C., and Medaglia, A.L., A review of dynamic vehicle routing problems, European Journal of Operational Research, 2013, Vol. 225, No. 1, pp. 1-11. https://doi.org/10.1016/j.ejor.2012.08.015
  25. Schilde, M., Doerner, K.F., and Hartl, R.F., Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem, European Journal of Operational Research, 2014, Vol. 238, No. 1, pp. 18-30. https://doi.org/10.1016/j.ejor.2014.03.005
  26. Sheridan, P.K., Gluck, E., Guan, Q., Pickles, T., Balciog, B., and Benhabib, B., The dynamic nearest neighbor policy for the multi-vehicle pick-up and delivery problem, Transportation Research Part A : Policy and Practice, 2013, Vol. 49, pp. 178-194. https://doi.org/10.1016/j.tra.2013.01.032
  27. Shrimpf, G., Schneider, J., Stamm-Wilbrandt, H., and Dueck, G., Recording breaking optimization results using the ruin and recreate principle, Journal of Computational Physics, 2000, Vol. 159, pp. 139-171. https://doi.org/10.1006/jcph.1999.6413
  28. Taillard, E., Badeau, P., Gendreau, M., Guertin, F., and Potvin, J.-Y., A tabu search heuristic for the vehicle routing problem with soft time windows, Transportation Science, 1997, Vol. 31, No. 2, pp. 170-186. https://doi.org/10.1287/trsc.31.2.170
  29. Taillard, E., Parallel iterative search methods for vehicle routing problems, Networks, 1993, Vol. 23, No. 8, pp. 661-673. https://doi.org/10.1002/net.3230230804
  30. Taillard, E.D., Gambardella, L.M., Gendreau, M., and Potvin, J.-Y., Adaptive memory programming : A unified view of metaheuristics, European Journal of Operational Research, 2001, Vol. 135, No. 1, pp. 1-16. https://doi.org/10.1016/S0377-2217(00)00268-X
  31. Van Hemert, J.I. and La Poutre, J.A., Dynamic routing problems with fruitful regions : Models and evolutionary computation, in Parallel Problem Solving from Nature-PPSN VIII, 2004.
  32. Yang, J., Li, J., Chen, Y., and Liu, X., Multi-Objective Distribution Model and Algorithm for Online Shopping Express Logistics, Journal of Computers, 2013, Vol. 8, No. 10, pp. 2558-2564.
  33. Zhu, K.Q. and Ong, K.-L., A reactive method for real time dynamic vehicle routing problem, in 2000 IEEE 24th International Conference on Tools with Artificial Intelligence, IEEE Computer Society, 2000.