Skip to main content
SpringerLink
Log in

Optimizing Service Level Agreements in Peer-to-Peer Supply Chain Model for Complex Projects Management

  • Conference paper
  • First Online:
Informatics in Economy (IE 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 273))

Included in the following conference series:

  • 507 Accesses

Abstract

The focus of this paper is to find appropriate approaches to facilitate end-to-end SLA (Service Level Agreements) in complex projects environments using Peer-to-Peer Supply Chain Model, to establish and enforce service levels between each pair of component consumer/provider, so that the overall project requirements can be achieved at the best utility value (SLA). The Supply Chain Formation problem is described in terms of a directed acyclic graph where the nodes are represented by the component suppliers/consumers. Intelligent agents send messages in the name of component suppliers/consumers on three constraints (scope, time, cost) giving raise to SLAs. The SLAs are expressed as utility functions and it is concluded that in complex projects scenario where the graph is always a tree the proposed model will converge to the optimal solution and the best utility value will be propagated autonomously across all component providers within the project environment.

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 EPUB and 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

References

  1. Barnes, M.: Time and money in contract control (1969)

    Google Scholar 

  2. ITIL Foundation Handbook, London, The Stationery Office (2012)

    Google Scholar 

  3. Penya-Alba, T., Vinyals, M., Cerquides, J., Rodriguez-Aguilar, J.A.: A scalable message-passing algorithm for supply chain formation. In: 26th Conference on Artificial Intelligence (AAAI 2012) (2012)

    Google Scholar 

  4. Winsper, M., Chli, M.: Decentralized supply chain formation using max-sum loopy belief propagation. Comput. Intell. 29, 280–309 (2012)

    MathSciNet  Google Scholar 

  5. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, vol. 1, 1st edn. Morgan Kaufmann, San Francisco (1988)

    MATH  Google Scholar 

  6. Collins, J., Ketter, W., Gini, M., Mobasher, B.: A multi-agent negotiation testbed for contracting tasks with temporal and precedence constraints. Int. J. Electron. Commer. 7, 35–58 (2002)

    Article  Google Scholar 

  7. Davis, R., Smith, R.G.: Negotiation as a metaphor for distributed problem solving. Artif. Intell. 20(1), 63–109 (1983)

    Article  Google Scholar 

  8. Walsh, W.E., Wellman, M.P., Ygge, F.: Combinatorial auctions for supply chain formation. In: Proceedings of the 2nd ACM Conference on Electronic Commerce, pp. 260–269 (2000)

    Google Scholar 

  9. Walsh, W.E., Wellman, M.P.: Decentralized supply chain formation: a market protocol and competitive equilibrium analysis. J. Artif. Intell. Res. (JAIR) 19, 513–567 (2003)

    MATH  Google Scholar 

  10. Cerquides, J., Endriss, U., Giovannucci, A., Rodriguez-Aguilar, J.A.: Bidding languages and winner determination for mixed multi-unit combinatorial auctions. In: IJCAI, pp. 1221–1226. Morgan Kaufmann Publishers Inc. (2003)

    Google Scholar 

  11. Giovannucci, A., Vinyals, M., Rodriguez-Aguilar, J.A., Cerquides, J.: Computationally-efficient winner determination for mixed multi-unit combinatorial auctions. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 2, pp. 1071–1078 (2008)

    Google Scholar 

  12. Winsper, M., Chli, M.: Decentralised supply chain formation: a belief propagation-based approach. In: Agent-Mediated Electronic Commerce (2010)

    Google Scholar 

  13. Winsper, M., Chli, M.: Decentralized supply chain formation using max-sum loopy belief propagation. Comput. Intell. 29(2), 281–309 (2013)

    Article  MathSciNet  Google Scholar 

  14. Norman, T.J., Preece, A., Chalmers, S., Jennings, N.R., Luck, M., Dang, V.D., Nguyen, T.D., Deora, V., Shao, J., Gray, W.A., et al.: Agent-based formation of virtual organisations. Knowl. Based Syst. 17(2), 103–111 (2004)

    Article  Google Scholar 

  15. Winsper, M.: Using min-sum loopy belief propagation for decentralised supply chain formation, Ph.D. thesis, Aston University (2012)

    Google Scholar 

  16. Bishop, C.M., et al.: Pattern Recognition and Machine Learning. Springer, New York (2006)

    MATH  Google Scholar 

  17. Farinelli, A., Rogers, A., Petcu, A., Jennings, N.R.: Decentralised coordination of low-power embedded devices using the max-sum algorithm. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 2, pp. 639–646 (2012)

    Google Scholar 

  18. Rogers, A., Farinelli, A., Stranders, R., Jennings, N.R.: Bounded approximate decentralised coordination via the max-sum algorithm. Artif. Intell. 175(2), 730–759 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  19. Kim, Y., Krainin, M., Lesser, V.: Application of max-sum algorithm to radar coordination and scheduling. In: Workshop on Distributed Constraint Reasoning (2010)

    Google Scholar 

  20. Pujol-Gonzalez, M., Cerquides, J., Meseguer, P., Rodríguez-Aguilar, J.A., Tambe, M.: Engineering the decentralized coordination of UAVs with limited communication range. In: Bielza, C., Salmerón, A., Alonso-Betanzos, A., Hidalgo, J.I., Martínez, L., Troncoso, A., Corchado, E., Corchado, J.M. (eds.) CAEPIA 2013. LNCS (LNAI), vol. 8109, pp. 199–208. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40643-0_21

    Chapter  Google Scholar 

  21. Stranders, R.: Coordinating teams of mobile sensors for monitoring environmental phenomena (2009)

    Google Scholar 

  22. McEliece, S.M.: The generalized distributive law. IEEE Trans. Inf. Theor. 46(2), 325–343 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  23. Koller, D., Friedman, N.: Probabilistic Graphical Models: Principles and Techniques. MIT Press, Cambridge (2009)

    MATH  Google Scholar 

  24. Winsper, M., Chli, M.: Using the max-sum algorithm for supply chain formation in dynamic multi-unit environments. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, vol. 3, pp. 1285–1286 (2012)

    Google Scholar 

  25. Weiss, Y.: Correctness of local probability propagation in graphical models with loops. Neural Comput. 12(1), 1–41 (2000)

    Article  Google Scholar 

  26. Weiss, Y., Freeman, W.T.: On the optimality of solutions of the max-product belief-propagation algorithm in arbitrary graphs. IEEE Trans. Inf. Theor. 47(2), 736–744 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  27. Vinyals, M., Cerquides, J., Farinelli, A., RodrguezAguilar, J.A.: Worst-case bounds on the quality of max-product fixed-points. In: NIPS, pp. 2325–2333 (2010)

    Google Scholar 

  28. Montresor, A., Jelasity, M.: PeerSim: a scalable P2P simulator. In: Proceedings of the 9th International Conference on Peer-to-Peer, pp. 99–100, Seattle, WA (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Business Informations Systems Department, “Babes-Bolyai” University, Cluj-Napoca, Romania

    Florina Livia Covaci

Authors
  1. Florina Livia Covaci
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Florina Livia Covaci .

Editor information

Editors and Affiliations

  1. Babeş-Bolyai University, Cluj-Napoca, Romania

    Gheorghe Cosmin Silaghi

  2. Babeş-Bolyai University, Cluj-Napoca, Romania

    Robert Andrei Buchmann

  3. Bucharest University of Economic Studies, Bucharest, Romania

    Catalin Boja

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Covaci, F.L. (2018). Optimizing Service Level Agreements in Peer-to-Peer Supply Chain Model for Complex Projects Management. In: Silaghi, G., Buchmann, R., Boja, C. (eds) Informatics in Economy. IE 2016. Lecture Notes in Business Information Processing, vol 273. Springer, Cham. https://doi.org/10.1007/978-3-319-73459-0_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73459-0_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73458-3

  • Online ISBN: 978-3-319-73459-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation