Collaborative Optimization of Vehicle and Crew Scheduling for a Mixed Fleet with Electric and Conventional Buses

Replacing conventional buses with electric is in line the concept of sustainable development. However, have disadvantages short driving range and high purchase price. Many cities must implement a semi-electrification strategy for bus routes. In this paper, bi-level, multi-objective programming model established collaborative scheduling problem vehicles drivers on route served by mixed fleet. The upper-layer minimizes operation cost economic carbon emission to optimize vehicle charging scheme; while lower-layer tries crew-scheduling scheme objective minimizing driver wages maximizing degree bus-driver specificity, considering impact drivers’ labor restrictions. Then, improved particle swarm algorithm based an ?-constraint processing mechanism used solve problem. Finally, actual taken as example verify effectiveness model. results show that can reduce unbalanced fleets crew scheduling, ensure driver–bus specificity standardize operation, save wage.