Skip to main content

Self-Organizing Logistics Process Control: An Agent-Based Approach

  • Conference paper

Part of the Communications in Computer and Information Science book series (CCIS,volume 271)

Abstract

Logistics networks face the contradictory requirements of achieving high operational effectiveness and efficiency while retaining the ability to adapt to a changing environment. Changing customer demands and network participants entering or leaving the system cause these dynamics and hamper the collection of information which is necessary for efficient process control. Decentralized approaches representing logistics entities by autonomous artificial agents help coping with these challenges. Coordination of these agents is a fundamental task which has to be addressed in order to enable successful logistics operations. This paper presents a novel approach to self-organization for multiagent system coordination. The approach avoids a priori assumptions regarding agent characteristics by generating expectations solely based on observable behavior. It is formalized, implemented, and applied to a logistics network scenario. An empirical evaluation shows its ability to approximate optimal supply network configurations in logistics agent coordination.

Keywords

  • Customer Satisfaction
  • Multiagent System
  • Supply Network
  • Logistics Network
  • Business Relationship

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brauer, W., Nickles, M., Rovatsos, M., Weiss, G., Lorentzen, K.F.: Expectation-Oriented Analysis and Design. In: Wooldridge, M.J., Weiß, G., Ciancarini, P. (eds.) AOSE 2001. LNCS, vol. 2222, pp. 226–244. Springer, Heidelberg (2002)

    CrossRef  Google Scholar 

  2. Collins, J., Youngdahl, B., Jamison, S., Mobasher, B., Gini, M.: A Market Architecture for Multi-Agent Contracting. In: Agents 1998, pp. 285–292. ACM Press, Saint Paul (1998)

    CrossRef  Google Scholar 

  3. Dittrich, P., Kron, T., Banzhaf, W.: On the Scalability of Social Order: Modeling the Problem of Double and Multi Contingency Following Luhmann. JASSS 6(1) (2003)

    Google Scholar 

  4. Finin, T., Fritzson, R., McKay, D., McEntire, R.: KQML as an agent communication language. In: Adam, N.R., Bhargava, B.K., Yesha, Y. (eds.) CIKM 1994, pp. 456–463. ACM, New York (1994)

    CrossRef  Google Scholar 

  5. Foundation for Intelligent Physical Agents: FIPA Agent Communication Language Specifications. Standard (2002)

    Google Scholar 

  6. Foundation for Intelligent Physical Agents: FIPA Request Interaction Protocol Specification. Standard (2002), document No. SC00026H

    Google Scholar 

  7. Horling, B., Lesser, V.: A Survey of Multi-Agent Organizational Paradigms. Know. Eng. Rev. 19(4), 281–316 (2005)

    CrossRef  Google Scholar 

  8. Horling, B., Mailler, R., Lesser, V.: A Case Study of Organizational Effects in a Distributed Sensor Network. In: Sonenberg, L., Sierra, C. (eds.) AAMAS 2004, pp. 1294–1295. IEEE Computer Society, New York (2004)

    Google Scholar 

  9. Hülsmann, M., Scholz-Reiter, B., Austerschulte, L., Wycisk, C., de Beer, C.: Autonomous Cooperation – A Way to Cope with Critical Incidents in International Supply Networks (ISN)? An Analysis of Complex Adaptive Logistic Systems (CALS) and their Robustness. In: 24th EGOS Colloquium, Vrije Universiteit Amsterdam (2008)

    Google Scholar 

  10. Hülsmann, M., Scholz-Reiter, B., Freitag, M., Wycisk, C., De Beer, C.: Autonomous Cooperation as a Method to cope with Complexity and Dynamics? – A Simulation based Analyses and Measurement Concept Approach. In: Bar-Yam, Y. (ed.) ICCS 2006, Boston (2006)

    Google Scholar 

  11. Luhmann, N.: Social Systems. Stanford University Press, Stanford (1995)

    Google Scholar 

  12. Montgomery, T.A., Durfee, E.H.: Search Reduction in Hierarchical Distributed Problem Solving. Group Decis. Negot. 2, 301–317 (1993)

    CrossRef  Google Scholar 

  13. Nickles, M., Rovatsos, M., Weiss, G.: Expectation-oriented modeling. Eng. Appl. Artif. Intel. 18(8), 891–918 (2005)

    CrossRef  Google Scholar 

  14. Nickles, M., Weiss, G.: Multiagent Systems Without Agents – Mirror-Holons for the Compilation and Enactment of Communication Structures. In: Fischer, K., Florian, M., Malsch, T. (eds.) Socionics. LNCS (LNAI), vol. 3413, pp. 263–288. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  15. Parsons, T., Shils, E. (eds.): Toward a General Theory of Action. Harvard University Press, Cambridge (1951)

    Google Scholar 

  16. Schillo, M., Spresny, D.: Organization: The Central Concept for Qualitative and Quantitative Scalability. In: Fischer, K., Florian, M., Malsch, T. (eds.) Socionics. LNCS (LNAI), vol. 3413, pp. 84–103. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  17. Schuldt, A.: Multiagent Coordination Enabling Autonomous Logistics. Doctoral dissertation, Universität Bremen (2010)

    Google Scholar 

  18. Schuldt, A.: Team Formation for Agent Cooperation in Logistics: Protocol Design and Complexity Analysis. In: Filipe, J., Fred, A. (eds.) ICAART 2011, pp. 398–405. SciTePress, Rome (2011)

    Google Scholar 

  19. Schuldt, A., Berndt, J.O., Herzog, O.: The Interaction Effort in Autonomous Logistics Processes: Potential and Limitations for Cooperation. In: Hülsmann, M., Scholz-Reiter, B., Windt, K. (eds.) Autonomous Cooperation and Control in Logistics. Springer, Heidelberg (to appear)

    Google Scholar 

  20. Schuldt, A., Gehrke, J.D., Werner, S.: Designing a Simulation Middleware for FIPA Multiagent Systems. In: Jain, L., Gini, M., Faltings, B.B., Terano, T., Zhang, C., Cercone, N., Cao, L. (eds.) WI-IAT 2008, pp. 109–113. IEEE Computer Society Press, Sydney (2008)

    Google Scholar 

  21. Tambe, M.: Towards Flexible Teamwork. J. Artif. Intell. Res. 7, 83–124 (1997)

    Google Scholar 

  22. Wooldridge, M., Jennings, N.R.: The Cooperative Problem-solving Process. J. Logic Comput. 9(4), 563–592 (1999)

    CrossRef  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Berndt, J.O. (2013). Self-Organizing Logistics Process Control: An Agent-Based Approach. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2011. Communications in Computer and Information Science, vol 271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29966-7_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29966-7_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29965-0

  • Online ISBN: 978-3-642-29966-7

  • eBook Packages: Computer ScienceComputer Science (R0)