Abstract
Taking into account the beginning of the postindustrial epoch and the consolidation of medical institutions, the inflow of patients is noticeable. The medication possibilities of the clinics are limited, which entails the need to rationalize the use of existing resources. Also, medical institutions tend to improve the quality of the treatment itself, which primarily involves increasing the satisfaction of patients with the services provided. Solving of this problem impossible without optimization, which begins with the construction of a set of quality criteria (vector criterion) and assessment of the conformity of the institutions work process to these criteria. In order to simplify the optimization problem, methods of curtailing the vector criteria are often used, that is, the aggregation of the set of criteria values. Quantitative methods may be used to assess the use of resources, such as medical equipment, or doctors working hours, but may not be used in all cases. An important aspect of the quality of treatment is also the assessment of the work of the institutions by the patients themselves, which in most cases is expressed in a qualitative form, which makes it practically impossible to apply classical approaches. The use of fuzzy logic methods can be an effective solution to the problem of curtailing the vector criterion, allowing to apply inaccurate expert knowledge about the domain for decision making without formalizing them in the form of traditional mathematical models. The article examines five criteria that influence the quality of the schedule with both the clients of medical institutions and the clinics themselves: • sufficient time for restoration of patients between procedures; • uniform distribution of the burden on medical personnel • maximizing equipment load; • comfortable group size for procedures; • A comfortable procedure for patient procedures. After analyzing these criteria and developing a fuzzy logic controller, an integral assessment of the quality of the schedule has been made, which can serve as a basis for further optimization and, consequently, a significant increase in the efficiency of the medical facilities.
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