| Summary: | 碩士 === 國立東華大學 === 電機工程學系 === 100 === This paper presents a novel multi-swarm sharing management for differential evolution (MSsDE) to deal with numerical optimization effectively. Multi-swarm is an effective search concept to keep the original search characteristic or effective balance strategies. Multi-swarm means several small swarm which has own strategy to cooperate search solution space , it will enhance the algorithm search ability in different problem, each swarm has to share its information to other swarms and remind other swarm of its explored situation. It not only balance the search characteristic but also enhance the evolution diversity.
However, it still has some defects need to overcome, such as weak search ability for smaller swarm and easy to fall into local optimal position. In order to overcome the problem mention above, the proposed multi-swarm sharing management can adjust each swarm size, share and analyze their information for other swarms to get more effective search ability. Testing and comparing results with original DE using different strategies. Adjust DE, EPUS-PSO, SPSO2011, SEGA by several benchmark functions, it showed that the proposed method has satisfying performance.
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