Study On The Development Of The Mathematical Model And Its Solution Alogrithm For Bus Transit Network Optimization

With the development of global economy and the rapid growth of the number of urbanpopulation and motor vehicle, most cities around the world, especially for the big cities,facehuge traffic pressure, which were mainly manifested in the severe traffic congestion,increasing traffic accidents, rising energy consumption, the deterioration of urbanenvironment etc. Traffic problem has become one of the factors to restrict the furtherdevelopment of urban economy in the world. Foreign successful experience showed that thepriority to development of urban public transport, establishing a efficient and reasonablepublic transport system can effectively alleviate the above problems, and for public transportsystem of any city, as the core content of bus transit planning, whether the result of networkdesign and optimization is reasonable or not directly affects the maneuverability andrationality of the public transportation planning.According to the above background, based on the analysis of the urban tra nsit networkoptimization research at home and abroad, taking the limited condition of urban publictransport capacity into consideration, this paper establishes a double objective optimizationmodel, aiming at minimizing the passenger transfer times and passenger travel time, thenuses the LINGO optimization software, combining with the question of small example toverify the accuracy of the model. Aiming at characteristics of optimization model constructedin this paper, we use genetic algorithm to solve the model to optimize the linhe district of thebayinnaoer city, finally generate optimization solution. By comparing the evaluation ofnetwork optimization index (the total length of network, the density of network, the sitecoverage, non-linear coefficient, etc.), we can find that, compared with the presentsituation,all the optimization of each evaluation index had a very big enhancement. Resultsshow that the established model and algorithm can be used for regular bus networkoptimization, the better results were obtained, and prove the accuracy and validity of themodel.