The Optimization Study on Passenger Organization at Large-scale Passenger Station during Rush Hours Based on Multi-Agent and Cellular Automata

The paper constructs multi-agent behavior decision model depending on the basic frame of cellular automata (CA) pedestrian flow. And Combine the passenger behavior with the decision of administrative department, basing on multi-agent simulation method of complex system theory, considering each advantage of CA and multi-agent, with the entrance of administrative departments and passenger behavior. In the passenger organization model involving in different kinds of agents such as passenger organization and passenger, which combines multi-agent with CA, the environment factor is expressed by CA. Individuals respond to the changes of environment around through the interaction between resource and the environment or negotiating with another individual. Through simulating the complex process of decision making of administrative departments, it brings forward the study way and the basic frame of the passenger organization optimization during rush hours of large-scale passenger station on complex adaptive system(CAS), constructs the optimization system of passenger organization during rush hours based on multi-agent, discusses the structure and the competing and cooperating relationship between each agent, and designs the optimization arithmetic based on evolutionary algorithm(EA) of multi-agent. At last, taking the optimization of passenger organization during rush hours at Guangzhou Station as the example to analysis and getting a good effect, this can offer the reference to the decision making of administrative departments.