Public Transport Optimal Dispatching Based On The Genetic-Newton Algorithm

With the rapid development of social economy and urbanization, increasing highly of urban Population and the number of car, the demand to traffic becomes higher and higher. The demand usually exceeds the transport capacity, and results in severe traffic congestion. Because urban public transit has the advantages of larger carry capacity, relatively less investment and lower road occupancy rate, in order to adapt to the urban development, so governments and related departments have strongly advocated that developing public transportations and improving the proportion of trip by bus. Improving the quality of bus dispatching management is very important to attract people to trip by bus. The bus dispatching is vital for public transportation management, so the research on bus dispatching optimization has more and more important practical significance.Traditional optimization methods and some modern intelligent algorithm are studied and compared in the thesis, based on their respective advantages and disadvantages, an algorithm which was combined with genetic algorithm and Newton is proposed. This algorithm make adaptive genetic algorithm and Newton algorithm combined. The adaptive crossover and mutation operators of the genetic algorithm ensure the direction of the hybrid algorithm to be convergent, and Newton algorithm increase the convergence speed of genetic algorithm.The bus optimization theory is introduced in this paper; balancing the interests of public transport company and passengers, the optimal schedule model of public transport was set up with the departure interval as the variable. Hybrid genetic algorithm which combined with genetic algorithm and Newton is proposed to optimize the schedule model. Using MATLAB to simulate the bus scheduling mode based on genetic-Newton algorithm, and the simulation results prove this algorithm is effective and superiority.