A Hybrid AI Approach to Staff Scheduling

  • Graham Winstanley
Conference paper

Abstract

Assigning staff to specific duties according to their contract, qualifications, skills, etc. within a working environment characterised by multi-disciplinarity and statutory regulations is problematic. This paper discusses an approach to nurse rostering, using a strategy of distributing the computational effort required in the scheduling process. The technique involves a hybrid approach that devolves responsibility for different aspects of the problem. In the pre-processing stage, the staff to be rostered are treated as semi-autonomous agents, each equipped with heuristics to guide their initial assignment. Compilation of individual rosters is followed by a scheduling phase in which a constraint solving agent applies constraint logic programming (CLP) techniques in the generation of ‘acceptable’ rosters.

Keywords

Monit Metaphor 

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References

  1. 1.
    Miller, H.E., Pierskalla, W.P., Rath G.J. Nurse scheduling using matematical programming, In Operations Research, Vol. 24, No.8, pp857–870, 1976.Google Scholar
  2. 2.
    Isken, M.W., Hancock W.M. A heuristic approach to nurse scheduling in hospital units with non-stationary, urgent demand and a fixed staff size, Journal of the Society for Health Systems, Vol. 2, No. 2, 1991.Google Scholar
  3. 3.
    Abdennadher, S., Schlenker, H. INTERDIP — An Interactive Constraint Based Nurse Scheduler, Proceedings of the 1st Int. Conf, on The Practical Application of Constraint Technologies and Logic Programming, PACLP99, London, 1999.Google Scholar
  4. 4.
    Cheng, B.M.W., Lee, J.H.M., Wu J.C.K. A Nurse Rostering System Using Constraint Programming and Redundant Modelling, IEEE Transactions on Information Technology in Medicine, Vol. l, pp44-54, 1997.CrossRefGoogle Scholar
  5. 5.
    Weigel R. Faltings V.B. Choueiry B.Y. Context in Discrete Constraint Satisfaction Problems, 12th European Conference on AI (ECAI96), pp205–209, Budapest, Hungary, 1996.Google Scholar
  6. 6.
    Scott, S., Simpson, R. Case Bases Incorporating Scheduling Constraint Dimensions: Experiences in Nurse Scheduling, In Advances in Case-Based Reasoning (EWCBR98), Springer Verlag Lecture Notes in AI, 1998.Google Scholar
  7. Shibutzit.www.shibutzit.com Accessed April 2002Google Scholar
  8. 8.
    Kumar, V. Algorithms for Constraint Satisfaction Problems: A Survey, AI Magazine Vol. 13, No. 1, pp 32–44, 1992.Google Scholar
  9. 9.
    Jaffar, J., maher M. Constraint Logic Programming: A Survey, Journal of Logic Programming, Vol. 19, No. 20, pp 503–582, 1994.MathSciNetCrossRefGoogle Scholar
  10. Nunez, J., Winstanley, G., Griffiths R.N. A Reluctance-Based Cost Distribution Strategy for Multi-Agent Planning, The International Journal of Applied Intelligence, Special Issue on Intelligent Adaptive Agents, Vol.9 pp39-55. Kluwer Academic Publishers, The Netherlands, 1998.Google Scholar
  11. 11.
    Freuder, E.C. Eliminating interchangeable values in constraint satisfaction problems, Proceedings of the 9th National Cnference on Artificial Intelligence (AAAI-91), pp227-233, 1991.Google Scholar
  12. 12.
    Wallace, M., Novello, S., Schimpf, J. ECLiPSe: A Platform for Constraint Logic Programming, IC-Parc, 1997.http://www.icparc.ic.ac.uk/eclipse/reports/eclipse/eclipse.html, Accessed July 2001.Google Scholar
  13. 13.
    Minton, S., Johnston, M.D., Philips A.B., Laird P. Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems, Artificial Intelligence, Vol. 58., pp 161-205, 1992.MathSciNetMATHCrossRefGoogle Scholar
  14. 14.
    Yokoo, M. Weak-commitment Search for Solving Constraint Satisfaction Problems, Proceedings of 12th Nat. Conf. On Artificial Intelligence, WA, USA, pp 313-318, 1994.Google Scholar

Copyright information

© Springer-Verlag London Limited 2003

Authors and Affiliations

  • Graham Winstanley
    • 1
  1. 1.School of Computing & Mathematical SciencesUniversity of BrightonUK

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