Integrated Approach to Vehicle Scheduling and Bus Timetabling for an Electric Bus Line

Abstract

Timetable and vehicle scheduling are important for transit operations. Electric buses are more environmentally friendly compared with conventional buses, and have been developing rapidly and may replace conventional buses in many cities worldwide. This paper focuses on the bus timetabling and vehicle scheduling problem for electric buses and develops a multiobjective optimization model for a single bus line operated with electric buses. The objectives include smoothing the vehicle departure intervals and minimizing the number of vehicles and total charging costs. The constraints reflect the limitations related to the range of departure intervals during different time periods, the vehicle operation mileage, and the charging conditions. A multiobjective particle swarm optimization (MOPSO) algorithm is developed to get the Pareto-optimal solution set. Considering the priority relationships among three objective components, an optimal solution selection strategy is developed. Compared to both the existing schedule and sequential schedule, the integrated model can not only effectively and efficiently reduce the number of vehicles and total charging costs, but also noticeably increase the smoothness of departure intervals. Moreover, it can allow the vehicle charging periods to be evenly distributed during off-peak hours.