Feeder Bus Network Optimization Scheduling Method Based on Particle Swarm Optimization

A feeder bus optimization scheduling model was put forward to improve the public transport sharing ability and solve bus optimization scheduling problem between rail transit and transportation origin destination in regular public transport. Different transportation demands between rail transit stations and transportation origin destination stations in different times were mainly considerate in the model, and then a multi-objective programming model was established. The multi-objective optimization model by using particle swarm optimization was analyzed and the optimal results under different situations were compared. Results show that the fixed value of buses in the team of the network optimization scheduling can meet the requirements of passengers in adjacent areas. The average load ratio is reduced significantly by using optimal operation. The viability of cost reduction of the proposed optimization model is also demonstrated.