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Afterword
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Author(s): E. Parsopoulos Konstantinos (University of Ioannina, Greece)and N. Vrahatis Michael (University of Patras, Greece)
Copyright: 2010
Pages: 4
Source title: Particle Swarm Optimization and Intelligence: Advances and Applications
Source Author(s)/Editor(s): Konstantinos E. Parsopoulos (University of Ioannina, Greece)and Michael N. Vrahatis (University of Patras, Greece)
DOI: 10.4018/978-1-61520-666-7.ch012

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Abstract

In the previous chapters, we presented the fundamental concepts and variants of PSO, as along with a multitude of recent research results. The reported results suggest that PSO can be a very useful tool for solving optimization problems from different scientific and technological fields, especially in cases where classical optimization methods perform poorly or their application involves formidable technical difficulties due to the problem’s special structure or nature. PSO was capable of addressing continuous and integer optimization problems, handling noisy and multiobjective cases, and producing efficient hybrid schemes in combination with specialized techniques or other algorithms in order to detect multiple (local or global) minimizers or control its own parameters.

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