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Hospitals are one of the core elements of a health care system that provide medical service to the patients. Many hospitals were built several years ago. Due to the absence of regular inspection on the structure, they are suffering from severe deterioration to the limit that some of these hospitals need to be demolished and re-constructed. This will significantly impact the service delivered by the health facilities. This paper presents Hospitals Rehabilitation Tradeoff (HORET) model utilizing Markov chains and genetic algorithms to provide a tradeoff between the rehabilitation costs and the number of unserved patients. HORET is comprised of four modules as follows, Database module, Markov chain deterioration module, rehabilitation cost optimization module, and multi-objective optimization for rehabilitation schedule. A case study comprised of four hospitals to validate the model and demonstrate its capabilities. The results showed 8% decrease in number of unserved patients and 20% saving in rehabilitation costs compared to actual scenarios.
Hospitals are one of the core elements of a health care system that provide medical service to the patients. Many hospitals were built several years ago. Due to the absence of regular inspection on the structure, they are suffering from severe deterioration to the limit that some of these hospitals need to be demolished and re-constructed. This will significantly impact the service delivered by the health facilities. This paper presents Hospitals Rehabilitation Tradeoff (HORET) model utilizing Markov chains and genetic algorithms to provide a tradeoff between the rehabilitation costs and the number of unserved patients. HORET is comprised of four modules as follows, Database module, Markov chain deterioration module, rehabilitation cost optimization module, and multi-objective optimization for rehabilitation schedule. A case study comprised of four hospitals to validate the model and demonstrate its capabilities. The results showed 8% decrease in number of unserved patients and 20% saving in rehabilitation costs compared to actual scenarios.
Multi-Objective Optimization for Rehabilitation of Heath Facilities
International Conference on Sustainable Infrastructure 2017 ; 2017 ; New York, New York
24.10.2017
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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