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以探索铁路枢纽客运组织方案的优化为目标,基于复杂系统理论中的多主体模拟方法,结合元胞自动机与多智能体各自的优势,将旅客行为与运输组织部门决策相结合,环境因素由元胞自动机表达,模型涉及到运输组织部门、旅客等不同类型的智能体,个体通过资源和环境的相互作用和与其他个体的交流协商来对周围环境的变化作出相应的反应。通过模拟运输组织部门复杂的决策过程,提出基于复杂适应系统理论的客运站客运组织优化的研究思路、基本框架和优化方法,探讨系统中各个智能体的结构及其竞合关系,设计基于多智能体的进化优化算法;最后以广州站高峰期客运组织优化为例进行了实证分析。
Based on the multi-agent simulation method in complex system theory, combined with the respective advantages of Cellular Automaton and Multi-Agent, this paper combines the passenger behavior with the decision of transport organization department. The environmental factors include Cellular automata express the model involving different types of agents, such as transport organization departments and travelers. Individuals respond to the changes of the surrounding environment through the interaction of resources and environment and the exchange and negotiation with other individuals. By simulating the complicated decision-making process of transport organization department, this paper puts forward the train of thought, basic framework and optimization method of passenger transport organization optimization based on complex adaptive system theory, discusses the structure of each agent in the system and its competition and cooperation, Body evolutionary optimization algorithm; Finally, the Guangzhou station peak passenger organization optimization as an example for empirical analysis.