A Novel Train Traffic Control Method Based on Time Petri Nets and Immune Quantum Optimization Algorithm

In this paper, a novel train traffic control method based on time Petri nets and immune quantum optimization algorithm is proposed. Considering the time uncertainty and self adjustment in the train running process, first of all, the time Petri net is used to simulate the train operation system. Because the quantum antibody code has high parallel performance in nature, the immune quantum optimization algorithm is used to search the global best solution. Experimental results show that the algorithm can speed up the search procession, which can overcome the problem that the ordinary search method is easy to trap in local optima to some extent.