Medical Imaging: Exams Planning and Resource Assignment - Hybridization of a Metaheuristic and a List Algorithm

Nathalie Klement, Nathalie Grangeon, Michel Gourgand

2017

Abstract

The presented work is about optimization of the hospital system. An existing solution is the pooling of resources within the same territory. This may involve different forms of cooperation between several hospitals. Problems of sizing, planning and scheduling may be considered. We define the problem of activities planning with resource assignment. To solve this problem, we propose a hybridization between a metaheuristic and a list algorithm. Single based metaheuristics are used. This proposition requires a new encoding inspired by permutation problems. This method is easy to apply: it combines already known methods. With the proposed hybridization, the constraints to be considered only need to be integrated into the list algorithm. For big instances, the solver used as a reference returns only lower and upper bounds. The results of our method are very promising. It is possible to adapt our method on more complex issues through integration into the list algorithm of the constraints. It would be particularly interesting to test these methods on real hospital authorities to assess their significance.

References

  1. Cardoen, B., Demeulemeester, E., and Beliën, J. (2010). Operating room planning and scheduling: A literature review. European Journal of Operational Research, 201(3):921-932.
  2. Coello, C. A. (2000). An updated survey of ga-based multiobjective optimization techniques. ACM Computing Surveys (CSUR), 32(2):109-143.
  3. Everett, J. (2002). A decision support simulation model for the management of an elective surgery waiting system. Health Care Management Science, 5(2):89-95.
  4. Garey, M. R. and Johnson, D. S. (1979). Computers and Intractability: A Guide to the Theory of NPcompleteness. WH Freeman and Company, New York.
  5. Gourgand, M., Grangeon, N., and Klement, N. (2014a). Activities planning and resource assignment on multiplace hospital system: Exact and approach methods adapted from the bin packing problem. In 7th International Conference on Health Informatics, Angers, France, pages 117-124.
  6. Gourgand, M., Grangeon, N., and Klement, N. (2014b). An analogy between bin packing problem and permutation problem: A new encoding scheme. In Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World, volume 438, pages 572-579.
  7. Johnson, D. S. (1973). Near-optimal bin packing algorithms. PhD thesis, Massachusetts Institute of Technology.
  8. Litvak, N., van Rijsbergen, M., Boucherie, R. J., and van Houdenhoven, M. (2008). Managing the overflow of intensive care patients. European journal of operational research, 185(3):998-1010.
  9. Rais, A. and Viana, A. (2011). Operations research in healthcare: a survey. International Transactions in Operational Research, 18(1):1-31.
  10. Santibán˜ez, P., Begen, M., and Atkins, D. (2007). Surgical block scheduling in a system of hospitals: an application to resource and wait list management in a british columbia health authority. Health care management science, 10(3):269-282.
  11. Silva, C., Klement, N., and Gibaru, O. (2016). A generic decision support tool for lot-sizing and scheduling problems with setup and due dates. In International Joint Conference - CIO-ICIEOM-IIE-AIM (IJC 2016), San Sebastian, Spain. ICIEOM.
  12. Trilling, L., Guinet, A., and Le Magny, D. (2006). Nurse scheduling using integer linear programming and constraint programming. IFAC Proceedings Volumes, 39(3):671-676.
  13. Van den Bergh, J., Beliën, J., De Bruecker, P., Demeulemeester, E., and De Boeck, L. (2013). Personnel scheduling: A literature review. European Journal of Operational Research, 226(3):367-385.
  14. VanBerkel, P. T. and Blake, J. T. (2007). A comprehensive simulation for wait time reduction and capacity planning applied in general surgery. Health care management Science, 10(4):373-385.
  15. Zhu, X. and Wilhelm, W. E. (2006). Scheduling and lot sizing with sequence-dependent setup: A literature review. IIE Transactions, 38(11):987-1007.
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Paper Citation


in Harvard Style

Klement N., Grangeon N. and Gourgand M. (2017). Medical Imaging: Exams Planning and Resource Assignment - Hybridization of a Metaheuristic and a List Algorithm . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017) ISBN 978-989-758-213-4, pages 260-267. DOI: 10.5220/0006113002600267


in Bibtex Style

@conference{healthinf17,
author={Nathalie Klement and Nathalie Grangeon and Michel Gourgand},
title={Medical Imaging: Exams Planning and Resource Assignment - Hybridization of a Metaheuristic and a List Algorithm},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)},
year={2017},
pages={260-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006113002600267},
isbn={978-989-758-213-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)
TI - Medical Imaging: Exams Planning and Resource Assignment - Hybridization of a Metaheuristic and a List Algorithm
SN - 978-989-758-213-4
AU - Klement N.
AU - Grangeon N.
AU - Gourgand M.
PY - 2017
SP - 260
EP - 267
DO - 10.5220/0006113002600267