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As the largest body of health care and treatment services to societies, in each hospital the human resource costs receive the great amount of considered budget and credit to the health and treatment sector of a country. Although determining the optimized number of staff needed for each ward of hospital is highly effective on the service quality, it is among the subject that any clear standards have not been written for it. This research has been done to set staff's shift schedule and determining the needed number of staff to increase the model hospital productivity and minimize its costs with…mehr

Produktbeschreibung
As the largest body of health care and treatment services to societies, in each hospital the human resource costs receive the great amount of considered budget and credit to the health and treatment sector of a country. Although determining the optimized number of staff needed for each ward of hospital is highly effective on the service quality, it is among the subject that any clear standards have not been written for it. This research has been done to set staff's shift schedule and determining the needed number of staff to increase the model hospital productivity and minimize its costs with help of intelligence systems. Since the presence of paints in the hospital and discharge them can be considered as a fragmented system, in the first step with Markov 's procedures specifications we can estimate wisely about the system conditions such as the number of needed beds and occupied beds which can be very useful for optimizing capacities usage. To develop the model, an approach is stated for minimizing the costs as the second step with assist of Petri's network. Finally, to control and to optimize, the model is presented with applying genetic algorithm for optimized shifting of huma
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Autorenporträt
Neda Darvish is PhD Student of Artificial Networking modeling in Physical-Technical Institute of Academy of Science of Republic of Tajikistan. She Interested in artificial networking Modeling and She has many articles in Intelligent Networking Approach Background.