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Seeker optimization algorithm:a novel stochastic search algorithm for global numerical optimization 被引量:15
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作者 Chaohua Dai Weirong Chen +1 位作者 Yonghua Song Yunfang Zhu 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2010年第2期300-311,共12页
A novel heuristic search algorithm called seeker op- timization algorithm (SOA) is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search... A novel heuristic search algorithm called seeker op- timization algorithm (SOA) is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empir- ical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in compari- son to differential evolution (DE) and three modified particle swarm optimization (PSO) algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms. 展开更多
关键词 swarm intelligence global optimization human searching behaviors seeker optimization algorithm.
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