Research of Multi-modal Function Optimization Based on Multi-Agent Immune Genetic Algorithm
To the deficiency of conventional genetic algorithm in solving multi-modal function optimization problem, the Multi-Agent technology in combination with immune principle was presented, in this new algorithm, the immune Agent dominant operator was provided, the operator can acquire the environment information from the evolution procedure, then real-time adjust and control the evolution operating, in order to find out the global optimum value quickly and efficiently. The simulation experiments indicates that the algorithm improves the deficiency of the genetic algorithm and is better than the conventional genetic algorithm, has the well ability of global and local search as well.
multi-Agent immune evolution genetic algorithm multi-modal optimization
Shurong Liu Xiangping Meng Wei Pang Hui Wang
School of Electrical and information Engineering Changchun Institute of Technology Changchun, Jilin,China
国际会议
哈尔滨
英文
3170-3173
2011-08-12（万方平台首次上网日期，不代表论文的发表时间）