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

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.
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  • HAL Id : hal-01494897, version 1
  • ENSAM : http://hdl.handle.net/10985/11663

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Nathalie Klement, Nathalie Grangeon, Michel Gourgand. Medical Imaging : Exams Planning and Resource Assignment : Hybridization of a Metaheuristic and a List Algorithm. 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF, Feb 2017, Porto, Portugal. pp.260-267. ⟨hal-01494897⟩

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