Adjustment of bus departure time of an electric bus transportation system for reducing costs and carbon emissions: A case study in Penghu

As a response to the worldwide problems of global warming and environmental pollution, electric vehicles have become the main direction of development in the automobile industry. Taking the bus system of Penghu Islands as the subject, this study explores the switching of all the original diesel buses to electric buses, and it adjusts the departure time of all the buses, with the purpose of reducing the costs of the construction and electricity used in an electric bus system. Plug-in and battery-swapping buses are used as examples in the study, and the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO) and Simulate Anneal Arithmetic (SA) algorithms, as well as an algorithm that combines the above, is used to optimize the departure times, in order not to affect the volumes and passenger demands in units of five minutes, the shift starts within the range of 15 minutes before or after the scheduled time. After each new schedule is prepared, batteries are used to optimize the daytime charging schedule of electric buses, to ensure the lowest cost of each new schedule. The results show that, regardless of which algorithm is used to optimize the departure time, all the minimum costs are lower than the best results before the adjustment, especially for the PSO-GA algorithm. Hence, the proper adjustment of the departure time can really reduce the construction and electricity costs and carbon emissions of the electric bus system.