Optimization Vehicle Scheduling Based on Simulated Annealing Genetic Algorithm

Abstract

It combines the own characteristics of vehicle scheduling, taking into account the both interests of the bus company and passengers, and establishes the vehicle scheduling plan model, taken the departure time (real value) as the gene variables to encode, and taken the difference between the adjacent grid spacing, the departure time interval of maximum and minimum, passenger load factor etc. to limit. With the example, the model is improved to optimize the solution. Finally, it is possible to reliably find an optimal or near-optimal solution program on vehicle scheduling optimization problem in transit huge search space. Through comparative analysis of the experimental results, it can verify the effectiveness of the improved algorithm and superiority.