Abstract
The paper focuses on Dynamic Vehicle Routing Problem with Time Windows, which generalizes its static counterpart by assuming that information about customers is not given a priori to the decision maker and it may change during the execution of the routes. Multi-Agent System to simulate and solve DVRPTW proposed by the author in his previous work has been extended in the paper. Taking into account different roles of the agents in the proposed system, two forms of cooperation (vertical and horizontal) between them have been implemented in the system. Whereas vertical cooperation refers to cooperation between different groups of agents, horizontal cooperation focuses on cooperation between agents belonging to the same group and/or working at the same level of the multi-agent system. Positive impact of different forms of cooperation on the results has been confirmed by a computational experiment.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Barbucha, D.: A multi-agent approach to the dynamic vehicle routing problem with time windows. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds.) ICCCI 2013. LNCS (LNAI), vol. 8083, pp. 467–476. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40495-5_47
Barbucha, D.: Influence of the waiting strategy on the performance of the multi-agent approach to the DVRPTW. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawiński, B. (eds.) ICCCI 2016. LNCS (LNAI), vol. 9875, pp. 464–473. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45243-2_43
Bellifemine, F., Caire, G., Greenwood, D.: Developing Multi-agent Systems with JADE. Wiley, Chichester (2007)
Braekers, K., Ramaekers, K., van Nieuwenhuyse, I.: The vehicle routing problem: State of the art classification and review. Comput. Ind. Eng. 99, 300–313 (2016)
Branchini, R.M., Armentano, A.V., Lokketangen, A.: Adaptive granular local search heuristic for a dynamic vehicle routing problem. Comput. Oper. Res. 36(11), 2955–2968 (2009)
Gendreau, M., Guertin, F., Potvin, J.-Y., Taillard, E.: Parallel tabu search for real-time vehicle routing and dispatching. Transp. Sci. 33(4), 381–390 (1999)
Hanshar, F.T., Ombuki-Berman, B.M.: Dynamic vehicle routing using genetic algorithms. Appl. Intell. 27, 89–99 (2007)
Khouadjia, M.R.: Solving dynamic vehicle routing problems: from single-solution based metaheuristics to parallel population based metaheuristics. Ph.D. thesis, Lille University, France (2011)
Kilby, P., Prosser, P., Shaw, P.: Dynamic VRPs: a study of scenarios. Technical report APES-06-1998, University of Strathclyde, Glasgow, Scotland (1998)
Laporte, G.: Fifty years of vehicle routing. Transp. Sci. 43(4), 408–416 (2009)
Larsen, A.: The dynamic vehicle routing problem. Ph.D. thesis, Institute of Mathematical Modelling, Technical University of Denmark (2001)
Montemanni, R., Gambardella, L.M., Rizzoli, A.E., Donati, A.V.: Ant colony system for a dynamic vehicle routing problem. J. Comb. Optim. 10(4), 327–343 (2005)
Pillac, V., Gendreau, M., Guéret, C., Medaglia, A.L.: A review of dynamic vehicle routing problems. Eur. J. Oper. Res. 225, 1–11 (2013)
Psaraftis, H.N., Wen, M., Kontovas, C.A.: Dynamic vehicle routing problems: three decades and counting. Networks 67(1), 3–31 (2016)
Smith, R.G.: The contract net protocol: high level communication and control in a distributed problem solver. IEEE Trans. Comput. 29(12), 1104–1113 (1980)
Solomon, M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper. Res. 35, 254–265 (1987)
Solomon, M.: VRPTW Benchmark problems. http://w.cba.neu.edu/msolomon/problems.htm
Srinivasan, D., Choy, M.C.: Hybrid multi-agent systems. In: Srinivasan, D., Jain, L.C. (eds.) Innovations in Multi-agent Systems and Applications - 1. SCI, vol. 310, pp. 29–42. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-14435-6_2
Toth, P., Vigo, D. (eds.): Vehicle Routing: Problems, Methods, and Applications, 2nd edn. Society for Industrial and Applied Mathematics Philadelphia, Philadelphia (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Barbucha, D. (2018). Solving DVRPTW by a Multi-agent System with Vertical and Horizontal Cooperation. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11056. Springer, Cham. https://doi.org/10.1007/978-3-319-98446-9_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-98446-9_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98445-2
Online ISBN: 978-3-319-98446-9
eBook Packages: Computer ScienceComputer Science (R0)