基于多智能体的铁路枢纽客运组织优化方法研究

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。

Passenger Organization Optimization Method at Rail Hub Based on Multi-Agent

To explore passenger organization optimization at rail hub,the paper combines the passenger behavior with the decision of administrative department based on multi-agent simulation method of complex system theory,considering each advantage of CA and multi-agent.In the model involving in different kinds of agents including passenger organization and passenger,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,the basic frame and the optimization method of the passenger organization optimization at rail hub on complex adaptive system（CAS）,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,the optimization of passenger organization during rush hours at Guangzhou Station is analyzed as an example.