Advertisement

Multiagent Based Scheduling of Elective Surgery

  • Sankalp Khanna
  • Timothy Cleaver
  • Abdul Sattar
  • David Hansen
  • Bela Stantic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7057)

Abstract

Scheduling of patients, staff, and resources for elective surgery in an under-resourced and overburdened public health system represents an inherently distributed class of problems. The complexity and dynamics of interacting factors demand a flexible, reactive and timely solution, in order to achieve a high level of utilization. In this paper, we present an Automated Scheduler for Elective Surgery (ASES) wherein we model the problem using the multiagent systems paradigm. ASES is designed to reflect and complement the existing manual methods of elective surgery scheduling, while offering efficient mechanisms for negotiation and optimization. Inter-agent negotiation in ASES is powered by a distributed constraint optimization algorithm. This strategy provides hospital departments with control over their individual schedules while ensuring conflict free optimal scheduling. We evaluate ASES to demonstrate the feasibility of our approach and demonstrate the effect of fluctuation in staffing levels on theatre utilization. We also discuss ongoing development of the system, mapping key challenges in the journey towards deployment.

Keywords

Multiagent Systems Distributed Constraint Optimization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Australian Medical Association: Public Hospital Report Card 2009 (2009), http://ama.com.au/node/5030
  2. 2.
    Bordini, R.H., Wooldridge, M., Hübner, J.F.: Programming Multi-Agent Systems in AgentSpeak using Jason. John Wiley & Sons (2007)Google Scholar
  3. 3.
    Burke, D.A.: Exploiting Problem Structure in Distributed Constraint Optimisation with Complex Local Problems. PhD thesis, Department of Computer Science, University College Cork, Ireland (2008)Google Scholar
  4. 4.
    Chechetka, A., Sycara, K.: An Any-Space Algorithm for Distributed Constraint Optimization. In: AAAI Spring Symposium on Distributed Plan and Schedule Management (2006)Google Scholar
  5. 5.
    Fox, M.S., Allen, B., Strohm, G.: Job-Shop Scheduling: An Investigation in Constraint-Directed Reasoning. In: 2nd Conference of The American Association for Artificial Intelligence, pp. 155–158 (1982)Google Scholar
  6. 6.
    Friha, L.: DISA: Distributed Interactive Scheduler using Abstractions, PhD thesis, University of Geneva, Geneva (1998)Google Scholar
  7. 7.
    Jebali, A., Hadj Alouane, A.B., Ladet, P.: Operating Rooms Scheduling. International Journal of Production Economics 99(1-2), 52–62 (2006)CrossRefGoogle Scholar
  8. 8.
    Jones, A., Rabelo, J.: Survey of Job Shop Scheduling Techniques. NISTIR, National Institute of Standards and Technology, Gaithersburg, USA (1998)Google Scholar
  9. 9.
    Khanna, S.: Distributed Constraint Optimization and Scheduling in Dynamic Environments. PhD Thesis, Institute for Integrated and Intelligent Systems, Griffith University, Australia (2010)Google Scholar
  10. 10.
    Khanna, S., Sattar, A., Hansen, D., Stantic, B.: An Efficient Algorithm for Solving Dynamic Complex DCOP Problems. In: 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2009), Milano, Italy, pp. 339–346 (2009)Google Scholar
  11. 11.
    Khanna, S., Sattar, A., Maeder, A., Stantic, B.: Intelligent Scheduling in Complex Dynamic Distributed Environments. In: 12th World Congress on Health (Medical) Informatics; Building Sustainable Health System (Medinfo 2007), Brisbane, Australia, pp. 1665–1666 (2007)Google Scholar
  12. 12.
    Krempels, K., Panchenko, A.: An Approach for Automated Surgery Scheduling. In: 6th International Conference on the Practice and Theory of Automated Timetabling, Brno, Czech Republic, pp. 209–233 (2006)Google Scholar
  13. 13.
    Krempels, K., Panchenko, A.: Dialog-Based Intelligent Operation Theatre Scheduler. In: 6th International Conference on the Practice and Theory of Automated Timetabling, Brno, Czech Republic, pp. 524–527 (2006)Google Scholar
  14. 14.
    Lamiri, M., Grimaud, F., Xie, X.: Optimization Methods for a Stochastic Surgery Planning Problem. International Journal of Production Economics, Special Issue on Introduction to Design and Analysis of Production Systems 120(2), 400–410 (2009)Google Scholar
  15. 15.
    Lamiri, M., Xie, X., Dolgui, A., Grimaud, F.: A Stochastic Model for Operating Room Planning with Elective and Emergency Demand For Surgery. European Journal of Operational Research 185(3), 1026–1037 (2008)MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Lass, R.N., Sultanik, E.A., Regli, W.C.: Dynamic Distributed Constraint Reasoning. In: 23rd AAAI Conference on Artificial Intelligence, Chicago, USA, pp. 1466–1469 (2008)Google Scholar
  17. 17.
    Modi, P.J., Shen, W., Tambe, M., Yokoo, M.: An Asynchronous Complete Method for Distributed Constraint Optimization. In: 2nd International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, pp. 161–168 (2003)Google Scholar
  18. 18.
    Paulussen, T., Zöller, A., Rothlauf, F., Heinzl, A., Braubach, L., Pokahr, A., Lamersdorf, W.: Agent-Based Patient Scheduling in Hospitals. In: Multiagent Engineering, Theory and Applications in Enterprises, pp. 255–275. Springer, Heidelberg (2006)Google Scholar
  19. 19.
    Petcu, A., Faltings, B.: A Scalable Method for Multiagent Constraint Optimization. In: Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, pp. 266–271 (2005)Google Scholar
  20. 20.
    Pham, D.N., Klinkert, A.: Surgical Case Scheduling as a Generalized Job Shop Scheduling Problem. European Journal of Operational Research 185(3), 1011–1025 (2008)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Prosser, P., Buchanan, I.: Intelligent Scheduling: Past, Present and Future. Intelligent Systems Engineering 3(2), 67–78 (1994)CrossRefGoogle Scholar
  22. 22.
    Queensland Health: Quarterly Public Hospitals Performance Report March Quarter 2010 (2010), http://www.health.qld.gov.au/surgical_access
  23. 23.
    Rao, A.S.: AgentSpeak(L): BDI Agents Speak Out in a Logical Computable Language. In: Perram, J., Van de Velde, W. (eds.) MAAMAW 1996. LNCS, vol. 1038, pp. 42–55. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  24. 24.
    Woolridge, M.: Introduction to Multiagent Systems, 2nd edn. John Wiley & Sons (2009)Google Scholar
  25. 25.
    Zweben, M., Fox, M.: Intelligent Scheduling. Morgan Kaufmann, San Francisco (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sankalp Khanna
    • 1
    • 2
  • Timothy Cleaver
    • 1
  • Abdul Sattar
    • 1
  • David Hansen
    • 2
  • Bela Stantic
    • 1
  1. 1.Institute for Integrated and Intelligent SystemsGriffith UniversityAustralia
  2. 2.The Australian e-Health Research CentreHerstonAustralia

Personalised recommendations