Cost Analysis and Optimization of Public Bus Fleets Using Genetic Algorithm Considering Different Technologies

This study examines the optimization of public bus fleets to reduce environmental impact and associated costs. By employing a Genetic Algorithm (GA), the research determines the optimal mix of electric, hydrogen, compressed natural gas, and diesel buses. The results show a clear preference for electric buses, primarily due to their significantly lower refuelling costs. The Genetic Algorithm effectively converges on a minimum-cost solution, demonstrating its utility in fleet optimization. The robustness of these findings is further validated through detailed simulation analysis. The study underscores the critical importance of adopting sustainable technologies in public transport systems, highlighting the benefits for both the environment and the operating companies. Additionally, it stresses the need for continuous monitoring of technological advancements and market trends. As technology and market dynamics evolve, staying informed is essential for making better decisions, and ensuring that investments in public transport infrastructure deliver maximum economic and environmental benefits.