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Adaptive immune-genetic algorithm for global optimization to multivariable function 被引量:9
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作者 Dai Yongshou Li Yuanyuan +2 位作者 Wei Lei Wang Junling Zheng Deling 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第3期655-660,共6页
An adaptive immune-genetic algorithm (AIGA) is proposed to avoid premature convergence and guarantee the diversity of the population. Rapid immune response (secondary response), adaptive mutation and density opera... An adaptive immune-genetic algorithm (AIGA) is proposed to avoid premature convergence and guarantee the diversity of the population. Rapid immune response (secondary response), adaptive mutation and density operators in the AIGA are emphatically designed to improve the searching ability, greatly increase the converging speed, and decrease locating the local maxima due to the premature convergence. The simulation results obtained from the global optimization to four multivariable and multi-extreme functions show that AIGA converges rapidly, guarantees the diversity, stability and good searching ability. 展开更多
关键词 immune-genetic algorithm function optimization hyper-mutation density operator.
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