Authors:
Nathalie Klement
1
;
Nathalie Grangeon
2
and
Michel Gourgand
2
Affiliations:
1
École Nationale Supérieure d’Arts et Métiers, France
;
2
Université Blaise Pascal, France
Keyword(s):
Hybridization, Metaheuristic, List Algorithm, Medical Imaging.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Healthcare Management Systems
;
Knowledge-Based Systems
;
Symbolic Systems
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. I
t would be particularly interesting to test these methods on real hospital
authorities to assess their significance.
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