基于混沌蚂蚁的分布式系统协同优化方法

摘要

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 importance for the design and modeling of CDS.%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.