Optimization of Urban Bus Stations Using Genetic Algorithm and GIS (Case Study: Tehran 6th District)

The design of standard bus stations is one of the most important issues that increase bus performance at the stations, reduce the take-off time and take passengers, and less negatively influence the traffic on other vehicles. In this research, we tried to find suitable locations for establishing subway station candidates in the city of Tehran 6 with GIS functions and ANP network analysis decision making. Using genetic algorithm and target functions, we aimed to optimize the candidate stations. In order to increase the accuracy of the research, the study area was divided into two areas of strong and weak concentration of service centers and commercial centers. the results showed that according to the network length and station spacing standards, area 6 requires 306 to 208 stations. Of the 291 stations, 247 stations, and 212 existing stations, 147 stations were optimized they can maximize demand coverage for demographic centers and absorbent centers.