Strengthen-reverse and reduction for particle swarm optimization
碩士 === 國立中央大學 === 電機工程學系 === 101 === This study aims to explore the problems of strengthen-reverse and reduction for particle swarm optimization. Genetic algorithm, particle swarm optimization and simulated annealing are widely used to search for the global optimal solutions of fitness functions. Th...
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| Format: | Others |
| Language: | zh-TW |
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2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/86154232760082899113 |
| Summary: | 碩士 === 國立中央大學 === 電機工程學系 === 101 === This study aims to explore the problems of strengthen-reverse and reduction for particle swarm optimization. Genetic algorithm, particle swarm optimization and simulated annealing are widely used to search for the global optimal solutions of fitness functions. The present work tries to make some improvements and to reduce the consuming time of the generalized optimization algorithms. Whether the generalized optimization algorithms are good or bad usually depends on the fitness function value.
This paper tried to use high pointing-behavior to make the speed of seeking out the global optimum being higher. But we need to increase the chance of escaping from the local optimal solutions. Final the new algorithms are as simplified as possible and that the user will apply these algorithms more easy than others. In addition, the simulation is given to verify the feasibility of the present method.
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