The Research Of Optimal Path Based On Improved Ant Colony Algorithm

In recent years,China's urban traffic problems have been paid more and more attention.China's major cities have to face the problems which urban traffic network developments failed to adapt to the growing traffic capacity.At present,the traffic congestion of several large cities is so serious that it has brought a great deal of inconvenience to residents.In order to improve the efficiency of urban transportation network,it's necessary to manufacture a set of intelligent transportation system which is not only suitable for the country but also included advanced computer technology as well as integrated GPS and GIS technology.It can solve the problem of traffic congestion,improve safety and the utilization of urban traffic.The characteristic of traffic network is that it can hardly obtain one exact solution by graph theory due to the scope of a city is too large.Therefore,to obtain one relatively satisfied solution through a small number of terms has become the focus.In view of this situation,the research put emphasis on the characteristic of urban traffic network and proposes an improved ant colony algorithm which enhances the capability of path search by modify pheromone in the region.Moreover,confirmed the optimized algorithm which proposed through the examples.Firstly,the research analyses the problems of current urban traffic and introduced data structures of traffic data as well as several commonly algorithms in the aspect of path searching.Furthermore,analyzed the advantages and disadvantages of them.Secondly,analyzed the feasibility of ant colony algorithm on solve the traffic path problem and realized the optimal traffic path algorithm model which based on the ant colony algorithm;introduced three current popular improved ant colony algorithms.Finally,the research brings forward an improved ant colony algorithm and determined optimal parameters by experiments.Moreover,compared and analyzed the improved ant colony algorithm with another improved ant colony algorithm which is popular currently.