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- W97494008 abstract "Particle Swarm Optimization (PSO) is a kind of group intelligent heuristic global evolution algorithm, which was proposed recently. It is used to solve complex optimization problems which are non-linear and non-differentiable, as well as combinatorial optimization problems. With advantages such as simple principle, it has fast convergence rate and it is liable to be implemented. Firstly, this paper proposes an improved PSO to search the global optimum of function after researching principle of the original one, as well as online and offline evaluation criterion of this improved algorithm. Secondly, an optimal algorithm is proposed to solve the problems with restrictions based on the combination of PSO and penalty function. Finally, analyzing the testing function and inertia weight, the paper affirms effectiveness of this improved algorithm through simulations. It is revealed that this improved algorithm is liable to search the global optimum of function and realize the global optimization." @default.
- W97494008 created "2016-06-24" @default.
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- W97494008 date "2012-01-01" @default.
- W97494008 modified "2023-09-23" @default.
- W97494008 title "Improved Particle Swarm Optimization Algorithm and Its Application to Global Optimization for Complex Function" @default.
- W97494008 cites W2109364787 @default.
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- W97494008 doi "https://doi.org/10.1007/978-3-642-27966-9_92" @default.
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