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The Art of Negotiation: Developing Efficient Agent-Based Algorithms for Solving Vehicle Routing Problem with Time Windows

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Industrial Applications of Holonic and Multi-Agent Systems

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8062))

Abstract

We present an ongoing effort in developing efficient agent-based algorithms for solving the vehicle routing problem with time windows. An abstract algorithm based on a generic agent decomposition of the problem is introduced featuring a clear separation between the local planning performed by the individual vehicles and the global coordination achieved by negotiation. The semantics of the underlying negotiation process is discussed as well as the alternative local planning strategies used by the individual vehicles. Finally a parallel version of the algorithm is presented based on efficient search diversification and intensification strategies. The presented effort is relevant namely for (i) yielding results significantly improving on all previous agent-based studies, (ii) the inclusion of relevant widely-used benchmarks missing from these studies and (iii) the breadth and depth of the provided evidence and analysis including relevant comparison to the state-of-the-art centralized solvers.

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References

  1. Bachem, A., Hochstattler, W., Malich, M.: The simulated trading heuristic for solving vehicle routing problems. Discrete Applied Mathematics 65(1-3), 47–72 (1996); First International Colloquium on Graphs and Optimization

    Article  MathSciNet  Google Scholar 

  2. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, part I route construction and local search algorithms. Transportation Science 39(1), 104–118 (2005)

    Article  Google Scholar 

  3. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, part II metaheuristics. Transportation Science 39(1), 119–139 (2005)

    Article  Google Scholar 

  4. Dan, Z., Cai, L., Zheng, L.: Improved multi-agent system for the vehicle routing problem with time windows. Tsinghua Science Technology 14(3), 407–412 (2009)

    Article  Google Scholar 

  5. Fischer, K., Müller, J.P., Pischel, M.: Cooperative transportation scheduling: an application domain for dai. Journal of Applied Artificial Intelligence 10, 1–33 (1995)

    Article  Google Scholar 

  6. Homberger, J., Gehring, H.: A two-phase hybrid metaheuristic for the vehicle routing problem with time windows. European Journal of Operational Research 162(1), 220–238 (2005)

    Article  Google Scholar 

  7. Kalina, P., Vokřínek, J.: Algorithm for vehicle routing problem with time windows based on agent negotiation. In: Proceedings of the 7th Workshop on Agents in Traffic and Transportation, AAMAS (2012)

    Google Scholar 

  8. Kalina, P., Vokřínek, J.: Improved agent based algorithm for vehicle routing problem with time windows using efficient search diversification and pruning strategy. In: Proceedings of the 3rd Workshop on Artificial Intelligence and Logistice (AILog) of the 2012 European Conference on Artificial Intelligence (ECAI), pp. 13–18 (2012)

    Google Scholar 

  9. Leong, H.W., Liu, M.: A multi-agent algorithm for vehicle routing problem with time window, pp. 106–111. ACM (2006)

    Google Scholar 

  10. Lim, A., Zhang, X.: A two-stage heuristic with ejection pools and generalized ejection chains for the vehicle routing problem with time windows. INFORMS Journal on Computing 19(3), 443–457 (2007)

    Article  MathSciNet  Google Scholar 

  11. Lu, Q., Dessouky, M.M.: A new insertion-based construction heuristic for solving the pickup and delivery problem with hard time windows. European Journal of Operational Research 175, 672–687 (2005)

    Article  Google Scholar 

  12. Nagata, Y., Bräysy, O.: A powerful route minimization heuristic for the vehicle routing problem with time windows. Operations Research Letters 37(5), 333–338 (2009)

    Article  MathSciNet  Google Scholar 

  13. Poon, P., Carter, J.: Genetic algorithm crossover operators for ordering applications. Computers and Operations Research 22(1), 135–147 (1995)

    Article  Google Scholar 

  14. Ropke, S.: Heuristic and exact algorithms for vehicle routing problems, PHD Thesis, Technical University of Denmark (2005)

    Google Scholar 

  15. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research 35, 254–265 (1987)

    Article  MathSciNet  Google Scholar 

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© 2013 Springer-Verlag Berlin Heidelberg

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Kalina, P., Vokřínek, J., Mařík, V. (2013). The Art of Negotiation: Developing Efficient Agent-Based Algorithms for Solving Vehicle Routing Problem with Time Windows. In: Mařík, V., Lastra, J.L.M., Skobelev, P. (eds) Industrial Applications of Holonic and Multi-Agent Systems. Lecture Notes in Computer Science(), vol 8062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40090-2_17

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  • DOI: https://doi.org/10.1007/978-3-642-40090-2_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40089-6

  • Online ISBN: 978-3-642-40090-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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