Multiple ODs routing algorithm for traffic systems using GA

The multiple origins multiple destinations routing (MOMDR) problem becomes extremely complicated when considering the traffic volumes on road sections. When solving this kind of problem, only heuristic algorithms have practical values because it is a typical NP-Hard problem. This paper applies Genetic Algorithm (GA) to enhance Sorting-Randomizing-Adjusting-Updating (SRAU) algorithm. The previous paper shows that different processing orders of the origin-destinations (ODs) result in different solutions with different performances. Therefore, an algorithm for finding the best processing order of ODs can optimize SRAU algorithm. In this paper, the processing order of ODs is transformed into a gene/chromosome of the individual of GA; then, the best gene can be found by evolution; finally, the best gene is transformed back to find the optimal solution of the problem. Sufficient simulations show that the proposed algorithm is more efficient than original SRAU algorithm. Comparisons also show that the proposed algorithm has higher performance and faster convergence speed than RAND algorithm which uses the random policy to find the proper processing order of ODs. Moreover, the consideration of the traffic volumes on the road sections enables the proposed algorithm to be applied to real traffic systems.