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Tytuł artykułu

Artificial intelligence technique for planning duties in hospital - preliminary results

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Treść / Zawartość
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Języki publikacji
EN
Abstrakty
EN
Scheduling doctors duties in a hospital are complicated and time-consuming tasks. The person responsible for creating a duty timetable is facing one major problem when allocating doctors to time periods: the agreement between several constraining (and often mutually excluding) requirements must be found. In this paper a solution methodology for the monthly duty assignment of doctors is presented. The typical problem is described in detail, along with specific hospital environment, from which datasets for experiments have been taken. A hybrid approach that utilizes strengths of a few artificial intelligence techniques was used to solve the problem. In particular, a population of initial solutions is generated heuristically and then improved using evolutionary algorithm. Experimental results are presented along with a discussion on the computational efficiency, operational acceptability and quality of the solutions.
Rocznik
Tom
Strony
KB83--90
Opis fizyczny
Bibliogr. 20 poz., tab.
Twórcy
  • Department of Computer Science, Wroclaw University of Technology
Bibliografia
  • 1. BURKE E.K., MACCARTHY B., PETROVIC S., QU R., Structured cases in case-based reasoning - re-using and adapting cases for time-tabling problems. Knowledge-Based Systems 13, 2000
  • 2. BURKE E. K., NEWALL J. P., WEARE R. F., A Simple Heuristically Guided Search for the Timetable Problem, Proceedings of the International ICSC Symposium on Engineering of Intelligent Systems, ICSC Academic Press, Nottingham, 1998
  • 3. BURKE E.K., PETROVIC S., Recent research directions in automated timetabling, European Journal of Operational Research 140, 2002
  • 4. CHEANG B., LI H., LIM A., RODRIGUES B., Nurse rostering problems - a bibliographic survey, European Journal of Operational Research 151, 2003
  • 5. COLORNI A., DORIGO M., MANIEZZO V., Genetic Algorithms and Highly Constrained Problems: the Time-Table Case, Proceedings of the First International Workshop on Parallel Problem Solving from Nature, Lecture Notes in Computer Science 496, 1990
  • 6. COLORNI A., DORIGO M., MANIEZZO V., Genetic Algorithms: a New Approach to the Time-Table Problem, Lecture Notes in Computer Science - NATO ASI Series, Vol. F 82, Combinatorial Optimization, 1990
  • 7. CORNE D., ROSS P., Puckish Initialization Strategies for Evolutionary Timetabling, Proceedings of the First International Conference on the Theory and Practice of Automated Timetabling, Napier University, Edinburgh 1995
  • 8. DO M.B., KAMBHAMPATI S., Planning as constraint satisfaction: Solving the planning graph by compiling it into CSP, Artificial Intelligence 132, 2001
  • 9. ERNST A.T., JIANG H., KRISHNAMOORTHY M., SIER D., Staff scheduling and rostering: A review of applications, methods and models, European Journal of Operational Research 153, 2004
  • 10. FOULDS L.R., JOHNSON D.G., SlotManager: a microcomputer-based decision support system for university timetabling, Decision Support Systems 27, 2000
  • 11. LEE S.-J., WU C.-H., CLXPERT: A Rule-Based Scheduling System, Expert Systems With Applications, Vol. 9, No. 2, 1995
  • 12. MARINAGI C.C., SPYROPOULOS C.D., PAPATHEODOROU C., KOKKOTOS S., Continual planning and scheduling for managing patient tests in hospital laboratories, Artificial Intelligence in Medicine 20, 2000
  • 13. MICHALEWICZ Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer Verlag, 1996
  • 14. MYSZKOWSKI P., NORBERCIAK M., Evolutionary Algorithms for Timetable Problems, Annales UMCS, Sectio Informatica, vol. I, Lublin 2003
  • 15. NEWALL J. P., Hybrid Methods for Automated Timetabling, PhD Thesis, Department of Computer Science, University of Nottingham 1999
  • 16. NORBERCIAK M., Feasible genotype initialization for evolutionary timetabling, Proceedings of 9th International Conference on Soft Computing MENDEL 2003, Brno 2003
  • 17. ROSS P., CORNE D., Comparing GA, SA and Stochastic Hillclimbing on Timetabling Problems. Evolutionary Computing; AISB Workshop, Sheffield 1995, Selected Papers, ed. T. Fogarty, Springer-Verlag Lecture Notes in Computer Science 993, 1995
  • 18. SPYROPOULOS C.D., AI planning and scheduling in the medical hospital environment, Artificial Intelligence in Medicine 20, 2000
  • 19. VALOUXIS C., HOUSOS E., Hybrid optimization techniques for the workshift and rest assignment of nursing personnel, Artificial Intelligence in Medicine 20, 2000
  • 20. YAKHNO T., TEKIN E.: Application of Constraint Hierarchy to Timetabling Problems, Proceedings of EurAsia-ICT 002, Springer-Verlag, 2002
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0013-0012
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