Real-Time Optimization of School Bus Routing Problem in Smart Cities Using Genetic Algorithm - ÖZMEN, MEHMET; ŞAHİN, HASAN (IEEE, 2021)
The smart city concept, which emerges as a result of the complex structure and major problems of cities, aims to make easy the life of the inhabitant in the urban areas, especially big cities which use IoT devices for the collecting and processing the data in the environment. By using these technologies smart healthcare, smart buildings, smart farming, smart energy planning, smart manufacturing, and smart transporting technologies can be developed. The optimization of school busses is also one of the critical application areas of smart cities that has a direct effect on the students' trip time to schools. In this problem, for collecting the students it is needed to optimize the path of the multiple busses by using different optimization techniques to choose the shortest and the convenient way. In this project, the school busses route problem of a company serving a school was solved with genetic algorithms by getting the related cost values in real-time by using the information from Google Maps. Experimental results showed that, as an evolutionary algorithm, genetic algorithm, can generate acceptable solutions for school busses' routing problems.
Proceedings of the 6th International Conference on Inventive Computation Technologies (Icict 2021)
Keywords: Smart Cities Transportation; Vehicle Routing Problem; Student Service Optimization; Genetic Algorithm; mTSP Optimization