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Research and Improvement of particle swarm optimization

Author: LiYuMao
Tutor: XingZhiDong
School: Northwestern University
Course: Computational Mathematics
Keywords: Swarm Intelligence Particle Swarm Optimization Artificial Fish School Algorithm Congestion factor Stage of evolution
CLC: O224
Type: Master's thesis
Year: 2009
Downloads: 465
Quote: 9
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Abstract


Particle swarm optimization studies and observations of birds foraging behavior of a swarm intelligence optimization algorithm . The algorithm is simple ideological , less parameters to be adjusted , convergence is fast and easy programming , and therefore by the attention and favor of the majority of scholars . In recent years it has become an important component of modern optimization methods and has shown great potential in function optimization , neural network training , engineering practice . Itself in the theoretical and practical aspects there are still a lot of inadequacies , in view of the particle swarm optimization algorithm easy to fall into the local optimum drawback , this paper gives an improved particle swarm algorithm and a hybrid optimization algorithm : particle swarm optimization strategy based on the stage of evolution in the new algorithm , the when judged algorithm may fall into local optimum , timely certain proportion to the number of particles re- assignment , so that the algorithm escape from local optima to the global minimum close. Numerical experiments show that the improved algorithm has greatly improved the accuracy and convergence speed . Second, particle swarm and fish hybrid optimization algorithm The algorithm analyzes the characteristics of the particle swarm and fish , fast convergence of particle swarm algorithm , but also to retain the optimal state of each particle through . Fish swarm algorithm has good ability of global optimization due to the introduction of the crowding factor . Combine the advantages of both hybrid optimization algorithm based on particle swarm and fish , by the classic function of the test , the hybrid optimization algorithm has satisfactory optimize performance .

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CLC: > Mathematical sciences and chemical > Mathematics > Operations Research > Optimization of the mathematical theory
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