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基于分布式协商进化算法的多Agent目标冲突消解
引用本文:杨萍,刘卫东,毕义明. 基于分布式协商进化算法的多Agent目标冲突消解[J]. 系统工程与电子技术, 2009, 31(8): 1918-1922
作者姓名:杨萍  刘卫东  毕义明
作者单位:第二炮兵工程学院, 陕西, 西安, 710025
基金项目:第二炮兵工程学院创新人才资助项目(xy200703)资助课题 
摘    要:
针对多Agent系统研究中的目标冲突消解问题,建立了在多个Agent的局部目标和系统全局目标间进行协调优化的多目标优化模型.在多Agent分布式规划的框架下,提出了一种基于遗传算法(genetic algorithm,GA)的分布式协商进化算法,用于求解多目标规划模型.针对GA搜索中保持解的多样性、提高收敛速度等问题,对选择算子进行了设计.通过仿真实验,证明新的选择算子能有效提高解的质量.最后将该算法应用于部队机动协同路线规划的目标冲突消解问题,验证了其有效性.

关 键 词:多Agent系统  目标冲突消解  多目标优化  分布式协商进化算法  遗传算法  Pareto最优解
收稿时间:2008-07-25
修稿时间:2009-01-08

Goal conflict resolution of multi-agent systems based on distributed negotiation evolution algorithm
YANG Ping,LIU Wei-dong,BI Yi-ming. Goal conflict resolution of multi-agent systems based on distributed negotiation evolution algorithm[J]. System Engineering and Electronics, 2009, 31(8): 1918-1922
Authors:YANG Ping  LIU Wei-dong  BI Yi-ming
Affiliation:The Second Artillery Engineering Coll., Xi'an 710025, China
Abstract:
In order to deal with goal conflict resolution in the research of multi-agent systems,a multi-objective optimization model is presented to search for some compromise among coordinate local goals of multi-agent and collective goals of systems.Under the distributed planning frame of multi-agent,a distributed negotiation evolution algorithm based on the genetic algorithm(DNEAGA) which is used for solving multi-objective programming model is proposed.In order to keep the solutions diversity and increase the convergence speed,a selection operator in genetic algorithm is designed.Simulation experiments show that the new selection operator can improve the solutions quality effectively.Finally,the DNEAGA is applied to solving the goal conflict in maneuver route planning of operations,and the effectiveness of the proposed algorithm is verified.
Keywords:
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