Disdussion Of Alogorithm And Application In Solving Transferred Paths Of Orbital Transportation

Because of its large capacity, low-energy, fast, punctual, safe, comfortable and so on, orbital transportation has gradually become an important component of urban public transport system and people's first choice for travel. More and more cities have been or will be conditional to begin the planning and construction of orbital transportation.As the construction of different lines are at different sections and times ,they may be operated by different operation business. It is necessary to build reasonable traffic ticket income distribution method to protect the interests of operators. With the continued construction of orbital transportation lines, the coupling in the lines will become increasingly high, and transfer across different lines will become increasingly frequent. In order to providing fair and reasonable services for income split, the establishment of a comprehensive settlement of the ticketing system has became an urgent need for the development of orbital transportation.The author studied a lot of literature and material in Chinese and abroad, and analyzed and compared the current four major sub-models. There are several problems in accuracy, rationality and cost. So they are all not suitable for practical application. On this basis, transferred path is the key to solve the problem of distribution. According to the benefit distribution depend on transferred paths in orbital transportation, the article designed an improved genetic algorithm for paths optimization. The algorithm combines Dijkstra algorithms, traverse algorithm thinking to design the initial population, which can ensure the effectiveness of individual paths to improve the quality of initial population. Niche technology in retaining the best is combined in selection. It can retain the optimal solution, but also to ensure the diversity of groups. Crossover Occurs in repeated nodes and there is only a bit of crossover, which can prevent creating a circuit or a loop to to ensure the smooth progress of the evolutionary process. Mutation operation combines the method for initial population and removing the ring in cross-operation.Finally, the apropriate parameters for this problem are set by the data of simulation experiments,which proved the convergence and the feasibility too.