MultiModal Immune Algorithm Based on Peaks Poised and Gradient Evolution Strategies
YANG KongYu1,2, WANG XiuFeng3
1.College of Computer Information Engineering, Shandong University of Finance, Jinan 250014 2.College of Information and Electrical Engineering, Shandong University of Architecture and Engineering, Jinan 250101 3.College of Information Technology and Science, Nankai University, Tianjin 300071
Abstract：Some available multimodal optimization algorithms are analyzed and the faults of them are pointed out. Based on their same features that they all have fine search effect to functions with equivalence peaks, the peaks poised strategy is proposed. Then a new Multimodal Immune Algorithm (MIA) with mechanisms of antibody evolution in immune system and conventional gradient evolution is designed. The implementations of peaks poised strategy and main evolution operators are given, the algorithm's operating mechanisms, complete convergence and computation complicacy are analyzed. The simulation experiments are performed and the results testify that MIA has availability on solving multimodal optimization problems, especially for functions with nonequivalence peaks, complete convergence and quickly convergence ability.
杨孔雨，王秀峰. 基于平衡峰值和梯度进化策略的多模态免疫算法*[J]. 模式识别与人工智能, 2006, 19(2): 167-172.
YANG KongYu, WANG XiuFeng. MultiModal Immune Algorithm Based on Peaks Poised and Gradient Evolution Strategies. , 2006, 19(2): 167-172.
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2006, Vol. 19 
