Research on the Optimization of Intelligent Bus Scheduling Based on QPSO Algorithm
In view of the city intelligent bus scheduling optimization problem, based on the full consideration of the bus company operating costs and the passengers waiting costs, establishes a bus scheduling optimization model with three goals by introducing an additional factor, i.e., the comfort of passengers. By means of the linear weighted method, integrates three objective functions. Since the particle swarm optimization algorithm is easy to fall into local optimum, uses the QPSO to achieve the optimal solution of bus departure interval by its capacity of judging precocious phenomena and jumping out of local optimum.
Intelligent Bus SchedulingComfort of PassengersLinear WeightedQuantum Particle Swarm OptimizationDeparture Interval
NETL
NSTL
万方数据
维普
