Abstract
The Multiagent Systems paradigm offers expressively rich and natural fit mechanisms for modeling and negotiation for solving distributed problems. Solving complex and distributed real world problems in dynamic domains however presents a significant challenge and requires the integration of technology innovation and domain expertise to create intelligent solutions. Scheduling of patients, staff, and resources for elective surgery in an under-resourced and overburdened public health system presents an excellent example of this class of problems. In this paper, we discuss the research challenges presented by the problem and outline our efforts of applying distributed constraint optimization, intelligent decision support, and prediction based theater allocation to address these challenges. We also discuss how these technologies can be used to drive better planning and change management in the context of surgery scheduling.
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References
Australian Medical Association. Public Hospital Report Card 2009 (October 2009), http://ama.com.au/node/5030
Bordini, R.H., Wooldridge, M., Hübner, J.F.: Programming Multi-Agent Systems in AgentSpeak using Jason. John Wiley & Sons (2007)
Boyle, J., Jessup, M., Crilly, J., Green, D., Lind, J., Wallis, M., Miller, P., Fitzgerald, G.: Predicting emergency department admissions. Emergency Medicine Journal (June 2011)
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)
Chechetka, A., Sycara, K.: An any-space algorithm for distributed constraint optimization. In: Proceedings of AAAI Spring Symposium on Distributed Plan and Schedule Management (March 2006)
Friha, L.: DISA: Distributed Interactive Scheduler using Abstractions. PhD thesis, University of Geneva, Geneva (July 1998)
Jebali, A., Hadj Alouane, A.B., Ladet, P.: Operating rooms scheduling. International Journal of Production Economics 99(1-2), 52–62 (2006)
Jones, A., Rabelo, J.: Survey of job shop scheduling techniques (1998)
Khanna, S.: Distributed Constraint Optimization and Scheduling in Dynamic Environments. PhD Thesis, Institute for Integrated and Intelligent Systems, Griffith University, Australia (2010)
Khanna, S., Sattar, A., Hansen, D., Stantic, B.: An Efficient Algorithm for Solving Dynamic Complex DCOP Problems. In: WI-IAT 2009: Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, pp. 339–346 (2009)
Khanna, S., Sattar, A., Maeder, A., Stantic, B.: Intelligent Scheduling in Complex Dynamic Distributed Environments. In: Medinfo 2007: Proceedings of the 12th World Congress on Health (Medical) Informatics; Building Sustainable Health Systems, Brisbane, Australia, pp. 1665–1666 (2007)
Krempels, K., Panchenko, A.: An Approach for Automated Surgery Scheduling. In: 6th International Conference on the Practice and Theory of Automated Timetabling, pp. 209–233 (2006)
Krempels, K.-H., Panchenko, A.: Dialog-based intelligent operation theatre scheduler. In: Burke, H.R.E.K. (ed.) 6th International Conference on the Practice and Theory of Automated Timetabling, pp. 524–527. Masaryk University, Brno (2006)
Lamiri, M., Grimaud, F., Xie, X.: Optimization methods for a stochastic surgery planning problem. International Journal of Production Economics 120(2), 400–410 (2009); Special Issue on Introduction to Design and Analysis of Production Systems
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)
Lass, R.N., Sultanik, E.A., Regli, W.C.: Dynamic distributed constraint reasoning. In: Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, Chicago, pp. 1466–1469 (2008)
Lesser, V., Ortiz, C., Tambe, M. (eds.): Distributed Sensor Networks: A Multiagent Perspective (Edited book), vol. 9. Kluwer Academic Publishers (May 2003)
Maheswaran, R.T., Tambe, M., Bowring, E., Pearce, J.P., Varakantham, P.: Taking DCOP to the real world: Efficient complete solutions for distributed Multi-Event scheduling. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, vol. 1, pp. 310–317 (2004)
Mailler, R., Lesser, V.: Solving Distributed Constraint Optimization Problems Using Cooperative Mediation. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, vol. 1, pp. 438–445 (2004)
Modi, P.J., Shen, W., Tambe, M., Yokoo, M.: An asynchronous complete method for distributed constraint optimization. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, pp. 161–168 (2003)
Modi, P.J., Shen, W.-M., Tambe, M., Yokoo, M.: Adopt: Asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence 161(1-2), 149–180 (2005)
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)
Petcu, A., Faltings, B.: A scalable method for multiagent constraint optimization. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, pp. 266–271 (August 2005)
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)
Prosser, P., Buchanan, I.: Intelligent scheduling: Past, present and future. Intelligent Systems Engineering 3(2), 67–78 (1994)
Queensland Health. Quarterly Public Hospitals Performance Report March Quarter (2010), http://www.health.qld.gov.au/surgical_access
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)
Scerri, P., Modi, J., Shen, W.-M., Tambe, M.: Are multiagent algorithms relevant for real hardware?: a case study of distributed constraint algorithms. In: SAC 2003: Proceedings of the 2003 ACM Symposium on Applied Computing, pp. 38–44. ACM, New York (2003)
Schurr, N., Okamoto, S., Maheswaran, R.T., Scerri, P., Tambe, M.: Evolution of a teamwork model. In: Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation, pp. 307–327 (2005)
Woolridge, M.: Introduction to Multiagent Systems, 2nd edn. John Wiley & Sons, Inc. (2009)
Zhang, W., Xing, Z., Wang, G., Wittenburg, L.: An analysis and application of distributed constraint satisfaction and optimization algorithms in sensor networks. In: AAMAS 2003: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 185–192. ACM, New York (2003)
Zweben, M., Fox, M.: Intelligent scheduling. Morgan Kaufmann Publishers Inc., San Francisco (1994)
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Khanna, S., Sattar, A., Boyle, J., Hansen, D., Stantic, B. (2012). An Intelligent Approach to Surgery Scheduling. In: Desai, N., Liu, A., Winikoff, M. (eds) Principles and Practice of Multi-Agent Systems. PRIMA 2010. Lecture Notes in Computer Science(), vol 7057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25920-3_39
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DOI: https://doi.org/10.1007/978-3-642-25920-3_39
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