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A fuzzy solution approach with genetic algorithm for a new fuzzy queue multi-objective locating model with the possibility of creating congestion for health centers

DOI: 10.52547/ijie.1.2.1, PP. 1-12

Subject Areas: Industrial Engineering

Keywords: Maximum Coverage Allocation Location Model, Queuing Theory, Fuzzy Sets Theory, Congestion System

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Abstract

Health authorities have always faced the challenge of organizing health-related processes. One of the most important processes is locating health centers, clinics, hospitals, etc. Is. With increasing demand, efforts have been made to increase the efficiency of existing systems and the use of new efficient systems (their type of facilities and location) by health managers. Therefore, the use of new and efficient scientific methods in the direction of health planning has always been of interest to managers and researchers in this field. Considering the huge costs of establishing health centers and their importance, this important issue has been taken into consideration. Accordingly, in this paper, we have presented a multi-objective locating model with maximum coverage. In this model, the distance of centers from demand points, demand rates, and service rates are expressed as triangular fuzzy numbers and also queue theory has been used to improve the quality of the system.

Cite this paper

Eslami, P. and Mirbaha, A. A. (2021). A fuzzy solution approach with genetic algorithm for a new fuzzy queue multi-objective locating model with the possibility of creating congestion for health centers. International Journal of Innovation in Engineering (IJIE), e218. doi: http://dx.doi.org/10.52547/ijie.1.2.1.

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