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Effect of parameter selection on different topological structures for Particle Swarm Optimization algorithm Cover

Effect of parameter selection on different topological structures for Particle Swarm Optimization algorithm

By: Daniele Peri  
Open Access
|Nov 2019

Abstract

Particle Swarm Optimization is an evolutionary optimization algorithm, largely studied during the years: analysis of convergence, determination of the optimal coefficients, hybridization of the original algorithm and also the determination of the best relationship structure between the swarm elements (topology) have been investigated largely. Unfortunately, all these studies have been produced separately, and the same coefficients, derived for the original topology of the algorithm, have been always applied. The intent of this paper is to identify the best set of coefficients for different topological structures. A large suite of objective functions are considered and the best compromise coefficients are identified for each topology. Results are finally compared on the base of a practical ship design application.

Language: English
Page range: 199 - 207
Submitted on: Mar 5, 2019
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Accepted on: Oct 21, 2019
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Published on: Nov 18, 2019
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Daniele Peri, published by Italian Society for Applied and Industrial Mathemathics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.