Land use subject and optimization patterns are one of the basic urban issues that human beings are always offering models and solutions to maximize the use of land and its capabilities in a variety of applications. On the other hand, optimizing medical land use will facilitate individuals' access to services and it Cause spatial justice all around the city. The main purpose of this research is the location optimizing of medical land use and, in particular way hospitals in urban areas.In addition, this goal in terms of locating criteria is responsive to the needs of citizens and being in a good position.The case study for this research was the 17th district of Tehran. District 17 has a small size, high population density, and small grain, which means this district is facing many problems with providing service levels. Also, the lack of public services has become one of the main factors in reducing the population in this district. Moreover, medical land use as one of the most basic service levels in the region has 0.16 m per capita, which is lower than the standard per capita and the per capita of Tehran city. The data of this study were collected on a map of the city and analyzed by the Geographic Information System (GIS) and the application of the Boolean logic method, by integrating the information layers on the final map. Then the appropriate hospital deployment areas are determined. Ultimately, by genetic algorithm (GA), the optimal and best answer for solving this problem has been derived by defining multiple functions and using MATLAB software. The results of an analysis of the current situation of medical land use in the 17th district of Tehran indicate that the current spatial distribution of medical land use is showing a lack of proper access for citizens. This area has a severe shortage of medical land use that causes the optimal location of the medical land use and specifically the hospital to be on the main agenda of this research. In conclusion, the results of the research show that the proposed method, while considering populations, neighborhoods, land characteristics, and access, finds the best place for therapeutic use. Therefore, it can be effectively used to locate optimal therapeutic use.