Optimization Study Of Bus Scheduling Based On Genetic Algorithm

Genetic Algorithm, Genetic Algorithm is a collateral, self organized and self adapted algorithm specially adapted to deal with complicated questions, which is used for reference from biology natural selection and heredity function. Simulating anneal algorithm simulates heated melting metal anneal process. At a certain original temperature, as the temperature falling down, combining the probability, this algorithm can random search all the aim functions optimal solution in space. That is at the local optimal solution, the probability dap can tend to entirely optimum.Genetic simulating anneal algorithm is an optimizing algorithm, which combined with genetic and anneal algorithm. Genetic algorithm has a bad local searching ability, but has a strong entire searching process handling ability; however anneal algorithm has a strong local searching ability and a bad entire searching process handling ability. So we combine the two algorithm merits to cover their weakness.As the social economy high speed developing and the city's population increasing, urban resident traffic quantity is also increased which results to the traffic jam. Whether the traffic is smooth or not, is directly affect the efficiency of the economy and quality of people's life. Therefore, many countries'government increase the investment on public transport, but the investment can not be afforded by every government. Our country's current public transport dispatch is lagged, which caused many resources wasting. So we utilized"software"method, exploring urban public transport optimizing dispatch management ways, which has practical meanings.Public transport dispatch is public transport enterprise's core content, which has good relationships with economy profit and society benefit. This paper deduced the solutions, in which concerns both passengers and public transport benefit and through analogy functions defining the content for both sides. after configuring the parameters and situations, we set up the mathematical model, used different genetic algorithm methods and got different optimizing results, in which the self adapted genetic algorithm and genetic simulating anneal algorithm both got much better results compared to traditional method. On the foundation, finally, this paper designed thepublic transport sheet schedule.