Optimization Analysis of Bus Operation Scheduling Considering Passenger and Cargo Sharing under Uncertain Demand

In view of the problems faced during the ongoing development of public transport, such as departure intervals that are too long, low occupancy rates, difficulties making a profit, and high express delivery costs, bus operation and scheduling models that consider passenger and cargo sharing have been attracting attention. In this work, considering the interests of both bus companies and passengers, we propose a bus operation scheduling optimization model that ensures the largest revenue for urban and rural bus companies and the shortest travel time for passengers under uncertain demand. We also design a particle group genetic algorithm for use with this model. The results of a case study set in China demonstrate the feasibility and effectiveness of the model and algorithm.