ACO and CP Working Together to Build a Flexible Tool for the VRP

Negar ZakeriNejad, Daniel Riera, Daniel Guimarans

Abstract

In this paper a flexible hybrid methodology, combining Ant Colony Optimisation (ACO) and Constraint Programming (CP), is presented for solving Vehicle Routing Problems (VRP). The stress of this methodology is on the word ‘flexible’: It gives reasonably good results to changing problems without high solution redesign efforts. Thus a different problem with a new set of constraints and objectives requires no changes to the search algorithm. The search part (driven by ACO) and the model of the problem (included in the CP part) are separated to take advantage of their best attributes. This separation makes the application of the framework to different problems much simpler. To assess the feasibility of our approach, we have used it to solve different instances of the VRP family. These instances are built by combining different sets of constraints. The results obtained are promising but show that the methodology needs deeper communication between ACO and CP to improve its performance.

References

  1. Augerat, P., Belenguer, J. M., Benavent, E., Corbern, A., Naddef, D., and Rinaldi, G. (1995). Computational results with a branch and cut code for the capacitated vehicle routing problem. IMAG.
  2. Balseiro, S. R., Loiseau, I., and Ramonet, J. (2011). An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows. Computers & Operations Research, 38(6):954-966.
  3. Berbeglia, G., Cordeau, J.-F., and Laporte, G. (2012). A hybrid tabu search and constraint programming algorithm for the dynamic dial-a-ride problem. INFORMS Journal on Computing, 24(3):343355.
  4. Blum, C., Puchinger, J., Raidl, G. R., and Roli, A. (2011). Hybrid metaheuristics in combinatorial optimization: A survey. Applied Soft Computing, 11(6):4135-4151.
  5. Cáceres-Cruz, J., Arias, P., Guimarans, D., Riera, D., and Juan, A. A. (2014). Rich Vehicle Routing Problem: Survey. ACM Computing Surveys (CSUR), 47(2):32.
  6. Cáceres Cruz, J. d. J. (2013). Randomized Algorithms for Rich Vehicle Routing Problems: From a Specialized Approach to a Generic Methodology. Doctoral thesis.
  7. Dorigo, M. and Birattari, M. (2010). Ant colony optimization. In Encyclopedia of machine learning, pages 36- 39. Springer.
  8. Drexl, M. (2012). Rich vehicle routing in theory and practice. Logistics Research, 5(1-2):4763.
  9. Golden, B. L., Raghavan, S., and Wasil, E. A. (2008). The Vehicle Routing Problem: Latest Advances and New Challenges: latest advances and new challenges, volume 43. Springer.
  10. Imran, A., Salhi, S., and Wassan, N. A. (2009). A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem. European Journal of Operational Research, 197(2):509-518.
  11. Khichane, M., Albert, P., and Solnon, C. (2008). Integration of ACO in a constraint programming language. In Ant Colony Optimization and Swarm Intelligence, pages 84-95. Springer.
  12. Khichane, M., Albert, P., and Solnon, C. (2010). Strong combination of ant colony optimization with constraint programming optimization. In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, pages 232- 245. Springer.
  13. Laporte, G. (2009). Fifty years of vehicle routing. Transportation Science, 43(4):408416.
  14. Laporte, G., Gendreau, M., Potvin, J.-Y., and Semet, F. (2000). Classical and modern heuristics for the vehicle routing problem. International transactions in operational research, 7(4-5):285300.
  15. Laporte, G., Toth, P., and Vigo, D. (2013). Vehicle routing: historical perspective and recent contributions. EURO Journal on Transportation and Logistics, 2(1-2):14.
  16. Meyer, B. and Ernst, A. (2004). Integrating ACO and constraint propagation. In Ant Colony Optimization and Swarm Intelligence, pages 166-177. Springer.
  17. Pisinger, D. and Ropke, S. (2007). A general heuristic for vehicle routing problems. Computers & operations research, 34(8):24032435.
  18. Riera, D., Juan, A., Guimarans, D., and Pagans, E. (2009). A constraint programming-based library for the vehicle routing problem. In Proceedings of the 21st European Modeling and Simulation Symposium (EMSS 2009), pages 261-266.
  19. Rodríguez, A. and Ruiz, R. (2012). A study on the effect of the asymmetry on real capacitated vehicle routing problems. Computers & Operations Research, 39(9):2142-2151.
  20. Rossi, F., Van Beek, P., and Walsh, T. (2006). Handbook of Constraint Programming. Elsevier.
  21. Shaw, P. (2011). Constraint programming and local search hybrids. In Hybrid Optimization, pages 271-303. Springer.
  22. Solnon, C. (2010). Ant colony optimization and constraint programming. Wiley Online Library.
  23. Talbi, E.-G. (2013). Hybrid metaheuristics. Springer.
  24. Vidal, T., Crainic, T. G., Gendreau, M., and Prins, C. (2013). A unified solution framework for multiattribute vehicle routing problems. European Journal of Operational Research.
  25. Yu, B. and Yang, Z. Z. (2011). An ant colony optimization model: The period vehicle routing problem with time windows. Transportation Research Part E: Logistics and Transportation Review, 47(2):166181.
Download


Paper Citation


in Harvard Style

ZakeriNejad N., Riera D. and Guimarans D. (2016). ACO and CP Working Together to Build a Flexible Tool for the VRP . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 122-129. DOI: 10.5220/0005668101220129


in Bibtex Style

@conference{icores16,
author={Negar ZakeriNejad and Daniel Riera and Daniel Guimarans},
title={ACO and CP Working Together to Build a Flexible Tool for the VRP},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2016},
pages={122-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005668101220129},
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 - ACO and CP Working Together to Build a Flexible Tool for the VRP
SN - 978-989-758-171-7
AU - ZakeriNejad N.
AU - Riera D.
AU - Guimarans D.
PY - 2016
SP - 122
EP - 129
DO - 10.5220/0005668101220129