Skip to main content
SpringerLink
Log in

Agent-Based Approaches to Transport Logistics

  • Conference paper
Applications of Agent Technology in Traffic and Transportation

Part of the book series: Whitestein Series in Software Agent Technologies ((WSSAT))

Abstract

This paper provides a survey of existing research on agent-based approaches to transportation and traffic management. A framework for describing and assessing this work will be presented and systematically applied. We are mainly adopting a logistical perspective, thus focusing on freight transportation. However, when relevant, work of traffic and transport of people will be considered. A general conclusion from our study is that agent-based approaches seem very suitable for this domain, but that this still needs to be verified by more deployed system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abouaïssa, H., Nicolas, J.C., Benasser, A., Czesnalowicz, E., Formal specification of Multi-Agent Systems: Approach based on meta-models and high-level Petri-nets — Case study of a transportation systems, Second IEEE International Conference on Systems, Man and Cybernetics, Volume 5, IEEE Computer Society Press, 2002.

    Google Scholar 

  2. Adler, J.L., Satapathy, G., Manikonda, V., Bowles, B., Blue, V.J., A multi-agent approach to cooperative traffic management and route guidance, Transportation Research Part B, Vol. 39, pp. 297–318, 2005.

    Google Scholar 

  3. Allo, B., Guettier, C., Léubin, N., A demonstration of dedicated constraint-based planning within agent-based architectures for autonomous aircraft, IEEE International Symposium on Intelligent Control, pp. 31–38, 2001.

    Google Scholar 

  4. Balbo, F., Pinson, S., Toward a Multi-agent Modelling Approach for Urban Public Transportation Systems, Engineering Societies in the Agents World II, LNAI 2203, pp. 160–174, Springer, 2001

    Google Scholar 

  5. Ballou, R.H., Business Logistics Management, 4th Ed. Prentice Hall International, 1999.

    Google Scholar 

  6. Bergkvist M., Davidsson, P., Persson, J.A., and Ramstedt, L., A Hybrid Micro-Simulator for Determining the Effects of Governmental Control Policies on Transport Chains, Multi-Agent-Based Simulation IV, LNAI Vol. 3415, Springer, 2005.

    Google Scholar 

  7. Blum, J., Eskandarian, A., Enhancing intelligent agent collaboration for flow optimization of railroad traffic, Transport Research Part A, 2002.

    Google Scholar 

  8. Blum, J., Eskandarian, A., “Domain-specific genetic agents for flow optimization of freight railroad traffic, 8th International Conference on Computers in Railways, Wessex Institute of Technology, Lemnos, Greece, 2002.

    Google Scholar 

  9. Bouzid, M., On-line transportation Scheduling using Spatio-Temporal Reasoning, 10th International Symposium on Temporal Representation and Reasoning and Fourth International Conference on Temporal Logic, IEEE, 2003.

    Google Scholar 

  10. Brewer, P.J., Plott, C.R., A binary conflict ascending price (BICAP) mechanism for the decentralized allocation of the right to use railroad tracks, Int. Journal of Industrial Organisation, Vol. 14: 857–866, 1996.

    Google Scholar 

  11. Buchheit, M., Kuhn, N., Müller, J. P., Pischel, M., MARS: Modeling a multiagent scenario for shipping companies. European Simulation Symposium, Society for Computer Simulation, 1992.

    Google Scholar 

  12. Budenske, J., Newhouse, J., Bonney, J., Wu, J., Agent-based schedule validation and verification”, IEEE International Conference on Systems, Man, and Cybernetics, Vol. 1: 616–621, 2001.

    Google Scholar 

  13. Bürckert, H-J., Funk, P., Vierke, G., An intercompany dispatch support system for intermodal transport chains, 33rd Hawaii International Conference on System Science, 2000.

    Google Scholar 

  14. Burstein, M., Ferguson, G., Allen, J., Integrating agent-based mixed-initiative control with an existing multi-agent planning system, Fourth International Conference on MultiAgent Systems, pp. 389–390, 2000.

    Google Scholar 

  15. Böcker, J., Lind, J., Zirkler, B., Using a multi-agent approach to optimise the train coupling and sharing system, European Journal of Operational Research, Vol. 134:242–252, 2001.

    Google Scholar 

  16. Callantine, T., Prevôt, T., Battiste, V., and Johnson, W., Agent-based support for distributed air/ground traffic management simulation research, AIAA 2003–5371, Reston, VA, U.S.A, American Institute of Aeronautics and Astronautics, 2003.

    Google Scholar 

  17. Carrascosa, C., Rebollo, M., Vicente, J., Botti, V., A MAS Approach for Port Container Terminal Management: The Transtainer Agent. Proceedings of SCI, IFSR, 2001.

    Google Scholar 

  18. Choy, M.C., Srinivasan, D., Cheu, R.L., Cooperative, Hybrid Agent Architecture for Real-time traffic control, IEEE Transactions on Systems, Man and Cybernetics, Part A, Vol. 33, Issue 5, pp. 597–607, Sept. 2003.

    Google Scholar 

  19. Clearwater, S.H. (ed.), Market-Based Control: Some early lessons, World Scientific, 1996.

    Google Scholar 

  20. Cuppari, A., Guida, L., Martelli, M., Mascardi, V., Zini, F., Prototyping freight trains traffic management using Multi-Agent Systems, IEEE International Conference on Information, Intelligence and Systems, 1999.

    Google Scholar 

  21. Degano, C., Di Febbraro, A., Fornara, P., Fault diagnosis in an intermodal container terminal. 8th IEEE International Conference on Emerging Technologies and Factory Automation: 433–440, Vol. 2, 2001.

    Google Scholar 

  22. Degano, C., Pellegrino, A., Multi-Agent Coordination and Collaboration for Control and Optimization Strategies in an Intermodal Container Terminal, IEEE International Engineering Management Conference, 2002.

    Google Scholar 

  23. Dong, J-W., Li, Y-J., Agent-based design and organization of intermodal freight transportation systems, Second International Conference on Machine Learning and Cybernetics, pp. 2269–2274, 2003.

    Google Scholar 

  24. European Conference of Ministers of Transport, Terminology of Combined Transports, United Nations, Geneva, 2001.

    Google Scholar 

  25. Fernández, A., Alonso, E., Ossowski, S., A multiagent architecture for train fleet management, Fifth UK Workshop on Multi-Agent Systems, 2002.

    Google Scholar 

  26. Fernández, A., Alonso, E., Ossowski, S., A multiagent architecture for bus fleet management, Integrated Computer-Aided Engineering, Vol. 11(2), 2004.

    Google Scholar 

  27. Findler, N.V., Lo, R., Distributed artificial intelligence approach to air traffic control, Control Theory and Applications, Vol. 138(6): 515–524, 1991.

    Google Scholar 

  28. Findler, N.V., Elder, G.D., Multiagent coordination and cooperation in a distributed dynamic environment with limited resources, Artificial Intelligence in Engineering, Vol. 9(3): 229–238, 1995.

    Article  Google Scholar 

  29. Fischer, K., Chaib-draa, B., Müller, J. P., Pischel, M., Gerber, C., A Simulation Approach Based on Negotiation and Cooperation Between Agents: A Case Study, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Vol. 29(4): 531–545, 1999

    Google Scholar 

  30. France, J., Ghorbani A.A., A Multiagent System for Optimizing Urban Traffic, International Conference on Intelligent Agent Technology, IEEE, 2003.

    Google Scholar 

  31. Funk, P., Vierke, G., Bürckert, H-J., A Multi-Agent Systems Perspective on Intermodal Transport Chains, Logistik-Management-Tagung LMT-99, 1999

    Google Scholar 

  32. Gambardella, L. M., Mastrolilli, M., Rizzoli, A. E., Zaffalon, M., An optimization methodology for intermodal terminal management. Journal of Intelligent Manufacturing, Vol. 12(5–6): 521–534, 2001.

    Google Scholar 

  33. Gambardella, L.M., Rizzoli, A. E., Zaffalon, M., Simulation and planning of an inter-modal container terminal. Simulation 71(2): 107–116, 1998.

    Google Scholar 

  34. García-Serrano, A.M., Teruel Vioque, D., Carbone, F., Méndez, V.D., FIPA-compliant MAS development for road traffic management with a Knowledge-Based approach: the TRACKR agents, Challenges in Open Agent Systems’ 03 Workshop, 2003.

    Google Scholar 

  35. Goldsmith, S. Y., et al., A Multi-agent System for Coordinating International Shipping. Agent Mediated Electronic Commerce, First International Workshop on Agent Mediated Electronic Trading, Springer, 1998.

    Google Scholar 

  36. Henesey, L., Notteboom, T., and Davidsson, P., Agent-based simulation of stakeholders relations: An approach to sustainable port and terminal management. International Association of Maritime Economists Annual Conference, 2003(a).

    Google Scholar 

  37. Henesey, L., Wernstedt, F., Davidsson, P., Market-Driven Control in Container Terminal Management. 2nd International Conference on Computer Applications and Information Technology in the Maritime Industries, 2003(b).

    Google Scholar 

  38. Hernández, J.Z., Ossowski, S., García-Serrano, A., Multiagent architectures for intelligent traffic management systems, Transportation Research Part C, Vol. 10: 473–506, 2002

    Google Scholar 

  39. Iordanova, B.N., Air traffic knowledge management policy, European Journal of Operations Research, Vol. 146: 83–100, 2003.

    Article  MATH  Google Scholar 

  40. Itmi M., M. D., Pecuchet J.-P., Serin F., Villefranche L., Eco-problem solving for containers stacking. Systems, Man and Cybernetics, IEEE International Conference on Intelligent Systems for the 21st Century: vol. 4: 3810–3815, 1995.

    Google Scholar 

  41. Kohout, R., Erol, K., In-Time Agent-Based Vehicle Routing with a Stochastic Improvement Heuristic, 11th Conference on Innovative Applications of Artificial Intelligence, 1999

    Google Scholar 

  42. Košecká, J., Tomlin C., Pappas, G., Sastry, S., Generation of conflict resolution maneuvers in air traffic management, IEEE-RSJ International Conference on Intelligent Robots and Systems 97, 1997.

    Google Scholar 

  43. Lee, T.-W., Park, N-K., Lee, D-W., Design of Simulation System for Port Resources Availability in Logistics Supply Chain, International Association of Maritime Economists Annual Conference, 2002.

    Google Scholar 

  44. Ljungberg, M., Lucas, A., The OASIS Air Traffic Management System, Pacific Rim International Conference on Artificial Intelligence, Seoul, Korea, 1992.

    Google Scholar 

  45. Malone, T., Crowston, K.: The interdisciplinary study of coordination, ACM Computing Surveys, Vol. 26(1), 1994.

    Google Scholar 

  46. McGraw-Hill Encyclopedia of Science & Technology, www.accessscience.com/server-java/Arknoid/science/AS (2003-03-25).

    Google Scholar 

  47. Nguyen-Duc, M., Briot, J-P., Drogoul, A., An application of Multi-agent coordination techniques in air traffic management, International Conference on Intelligent Agent Technology, pp. 622–625, 2003.

    Google Scholar 

  48. Nwana, H.S., Lee, L., Jennings, N.R.: Co-ordination in software agents systems, BT Technol J. Vol. 14(4), 1996.

    Google Scholar 

  49. Painter, J.H., Cockpit multi-agent for distributed air traffic management, AIAA Guidance, Navigation, and Control Conference and Exhibit, 2002.

    Google Scholar 

  50. Parkes, D., Ungar, L., An auction-based method for decentralized train scheduling, AGENTS’01, 2001.

    Google Scholar 

  51. Parunak, H.V.D., Industrial and Practical Applications of DAI, In Multiagent Systems, (ed.) G. Weiss. MIT Press, 1999.

    Google Scholar 

  52. Parunak, H.V.D. Agents in Overalls: Experiences and Issues in the Development and Deployment of Industrial Agent-Based Systems, International Journal of Cooperative Information Systems 9(3): 209–227, 2000.

    Article  Google Scholar 

  53. Perugini, D., Lambert, D., Sterling, L., Pearce, A., Provisional Agreement Protocol for global Transportation Scheduling, International Workshop on Agents in Traffic and Transportation, New York, U.S.A., 2004.

    Google Scholar 

  54. Proshun, S-R., Carter, J., Field, T., Marshall, J., Polak, J., Schumacher K., Song, D-P., Woods, J., Zhang, J., Container World: Global agent-based modelling of the container transport business, 4th International Workshop on Agent-Based Simulation, Montpellier, France, 2003.

    Google Scholar 

  55. Rebollo, M., Vicente, J., Carrascosa, C., Botti, V., A MAS Approach for Port Container Terminal Management. 3rd Iberoamerican workshop on DAI-MAS, pp. 83–94, 2001.

    Google Scholar 

  56. Rizzoli, A., Funk, P., Gambardella L., An architecture for agent-based simulation of rail/road transport, International Workshop on Harbour, Maritime & Multimodal Logistics Modelling and Simulation, 2002.

    Google Scholar 

  57. Rizzoli A.E., Fornara N., Gambardella L.M., A Simulation tool for combined railroad transport in intermodal terminals, MODSIM 1999, Modelling and Simulation Society of Australia and New Zealand, 1999.

    Google Scholar 

  58. Sandholm, T., An implementation of the contract net protocol based on marginal cost calculations, Eleventh National Conference on Artificial Intelligence, 1993

    Google Scholar 

  59. Sawamoto, J., Tsuji, H., Koizumi, H., Continuous Truck Delivery Scheduling and Execution system with Multiple Agents, in Kuwabara, K. and Lee, J. (Eds.), PRIMA 2002, LNAI 2413, pp. 190–204, Springer, 2002.

    Google Scholar 

  60. Schneeweiss, C., Hierarchies in distributed decision making, Springer-Verlag, ISBN 3-540-65585-9, 1999.

    Google Scholar 

  61. Shillo, M., Vierke, G., Multidimensional utility vectors in the transportation domain, ECAI Workshop on Agent Technologies and Their Application Scenarios in Logistics, 2001.

    Google Scholar 

  62. Sjöland, T., Kreuger, P., Aronsson, M., Heterogenous Scheduling and Rotation, in A.C. Kakas, F. Sadri (Eds.): Computational Logic: Logic Programming and Beyond. Essays in Honour of Robert A. Kowalski, Part L LNAI 2407, Springer, 2002.

    Google Scholar 

  63. Stock, J. R. and D. M. Lambert, Strategic Logistics Management. Boston, U.S.A., McGraw-Hill Irwin, 2001.

    Google Scholar 

  64. Thurston, T. and H. Hu, Distributed Agent Architecture for Port Automation. 26th International Computer Software and Applications Conference, IEEE Computer Society, 2002.

    Google Scholar 

  65. Tomlin, C., Pappas, G.J., Sastry, S., Noncooperative conflict resolution, 36th Conference on Decision & Control, pp. 1816–1821, 1997.

    Google Scholar 

  66. Törnquist J., Davidsson P., A Multi-Agent System Approach to Train Delay Handling, ECAI-02 Workshop on Agent Technologies in Logistics, 2002.

    Google Scholar 

  67. van Katwijk, R.T., De Schutter, B., Hellendoorn, J., van Koningsbruggen, P., van Gosliga, S.P., A Test Bed For Multi-Agent Control Systems In Road Traffic Management, Workshop on Agents in Traffic and Transportation, New York, U.S.A., 2004.

    Google Scholar 

  68. van Katwijk, R., van Koningsbruggen, P., Coordination of traffic management instruments using agent technology, Transportation Research Part C, Vol. 10: 455–471, 2002.

    Google Scholar 

  69. Vilaplana, M. A., Goodchild, C., Application of distributed artificial intelligence in autonomous aircraft operations, 20th Conference on Digital Avionics Systems, Vol. 2, 2001.

    Google Scholar 

  70. Wangermann, J., Stengel, R., Distributed optimization and principled negotiation for advanced air traffic management, IEEE International Symposium in Intelligent Control, 1996.

    Google Scholar 

  71. Wangermann, J., Stengel, R., Principled negotiation between intelligent agents: a model for air traffic management, Artificial Intelligence in Engineering, Vol. 12: 177–187, 1998.

    Article  Google Scholar 

  72. Weiss G., Multi-Agent Systems, MIT Press, Cambridge, 1999.

    Google Scholar 

  73. Wollkind, S., Valasek, J., and Ioerger, T.R., Automated Conflict Resolution for Air Traffic Management Using Cooperative Multiagent Negotiation. AIAA Guidance, Navigation, and Control Conference, 2004.

    Google Scholar 

  74. Wooldridge M., An Introduction to Multi-Agent Systems, John Wiley & Sons, London, 2002.

    Google Scholar 

  75. Yi, D.W., Kim, S.H., Kim., N.H., Combined Modeling with Multi-Agent Systems and Simulation: Its Application to Harbor Supply Chain Management. 35th Hawaii International Conference on System Sciences, 2002.

    Google Scholar 

  76. Zhu, K., Bos, A., Agent-based design of intermodal freight transportation systems, NECTAR Conference, Delft, 1999.

    Google Scholar 

  77. Zhu, K., Ludema, M., van der Heijden, R., Air cargo transports by multi-agent based planning, 33rd Hawaii International Conference on System Science, 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Systems and Software Engineering, Blekinge Institute of Technology Soft Center, 372 25, Ronneby, Sweden

    Paul Davidsson, Lawrence Henesey, Linda Ramstedt, Johanna Törnquist & Fredrik Wernstedt

Authors
  1. Paul Davidsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lawrence Henesey
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Linda Ramstedt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Johanna Törnquist
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fredrik Wernstedt
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. of Artificial Intelligence and Applied Computer Science, University of Würzburg, Am Hubland, 97070, Würzburg, Germany

    Franziska Klügl

  2. Instituto de Informática, UFRGS, Campus do Vale, Bloco IV, Bairro Agronomia, Av. Bento Gonçalves, 91501-970, Porto Alegre, Brazil

    Ana Bazzan

  3. Al Group DIET, ESCET, Universidad Rey Juan Carlos, Campus de Móstoles, Calle Tulipán s/n, 28933, Madrid, Spain

    Sascha Ossowski

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Birkhäuser Verlag

About this paper

Cite this paper

Davidsson, P., Henesey, L., Ramstedt, L., Törnquist, J., Wernstedt, F. (2005). Agent-Based Approaches to Transport Logistics. In: Klügl, F., Bazzan, A., Ossowski, S. (eds) Applications of Agent Technology in Traffic and Transportation. Whitestein Series in Software Agent Technologies. Birkhäuser Basel. https://doi.org/10.1007/3-7643-7363-6_1

Download citation

  • DOI: https://doi.org/10.1007/3-7643-7363-6_1

  • Publisher Name: Birkhäuser Basel

  • Print ISBN: 978-3-7643-7258-3

  • Online ISBN: 978-3-7643-7363-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation