基于混沌蚂蚁的分布式系统协同优化方法  

Chaotic Ant Based Collaborative Optimization Algorithm in Distributed System

作　　者：魏臻[1] 葛方振[1,2] 陆阳[1] 王强[1] 李丽香[3] 

机构地区：[1]合肥工业大学计算机与信息学院,合肥230009 [2]准北师范大学计算机科学与技术学院,淮北235000 [3]北京邮电大学信息安全中心,北京100876

出　　处：《模式识别与人工智能》2013年第2期195-204,共10页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61070220,60873195);高等学校博士学科点专项科研基金项目(No.20090111110002);教育部霍英东教育基金会基金项目(No.121062);安徽省高等学校省级自然科学基金项目(No.KJ2011B147)资助

摘　　要：针对复杂分布式系统的优化问题,提出基于混沌蚂蚁的复杂分布式系统协同优化方法.在系统理论指导下,分析复杂分布式系统中自主Agent的基本动力学特征,进而提出复杂分布式系统协同优化模型.在此基础上,借助混沌蚂蚁群算法(CAS)的思想,建立基于混沌蚂蚁的复杂分布式系统协同优化算法(CAS-CO).通过对复杂多Agent网络中基于位置的任务分配问题进行仿真实验,同时与已有算法仿真结果对比,表明CAS-CO算法可行有效,反映文中模型的正确性和Agent的自主性在复杂分布式系统设计和构建中的重要性.To solve the optimization problem in complex distributed system （CDS）, a collaborative optimization method based on chaotic ant swarm in CDS is presented. The basic dynamic characteristics of complex distributed systems are analyzed under the guide of system theory, and a model of collaborative optimization of CDS is proposed. Thus, a collaborative optimization in CDS is established based on the idea of chaotic ant swarm （CAS）, called CAS based collaborative optimization （CAS-CO）. The locality-based task allocation in complex networked multi-agent system is resolved by CAS-CO, and the comparison results of the proposed algorithm and the existing ones show that the CAS-CO algorithm is feasible and effective, and the proposed model is correct and the autonomy of an agent is of imvortance for the design and modeling of CDS.

关 键 词：复杂分布式系统 协同优化模型 自主性 混沌蚂蚁群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]