Distributed Optimization of Subway Stations based on Anylogic and Swarm Intelligence Optimization Algorithms

Subway transportation undertakes the important task of urban passenger transportation and is closely related to the people’s livelihood and economic development of the city. It is of great practical significance to design a relatively reasonable evacuation channel model for the collection and distribution management of people in the subway, so as to provide passengers with reasonable path planning, reduce the investment of evacuation resources, and improve the efficiency and quality of subway operations. This paper takes the Wuhan subway station as the research object, establishes the subway personnel flow model through the Anylogic technology and the swarm intelligence optimization algorithm algorithm, takes the personnel collection path planning and the collection and distribution simulation model as the research content, and optimizes the path planning through the collection and distribution model. The results show that using the personnel distribution model optimized by the swarm intelligence optimization algorithm for path optimization can shorten the average entry time by 9 seconds and the average battle time by 30.9 seconds, which significantly improves the efficiency of personnel evacuation.