Ca-PSO: Coulomb attracting Particle Swarms
DOI:
https://doi.org/10.30973/progmat/2019.11.3/1Keywords:
Optimization Algorithm, Coulomb Law, Optimization Functions, Particle SwarmAbstract
This article presents a variant of the C-PSO algorithm, which we have called Ca-PSO, unlike C-PSO which considers lBesti and gBest as point charges to, Ca-PSO considers the particles xi and gBest as them. At the same time a comparison of four algorithms is presented: the original algorithm PSO (Particle Swarm Optimization), PSO with "constriction" (Constriction PSO), C-PSO a version that makes use of Coulomb's law and the proposed algorithm C-PSO. The schematic movement of a particle in the Ca-PSO algorithm is also shown. The results that are shown correspond to the mean of 50 runs, each algorithm has been executed 10000 iterations per function on 50 and 100 dimensions. The Ca-PSO algorithm showed a superior performance over the C-PSO in six of ten testing functions. Moreover, it is shown that both C-PSO and Ca-PSO present a better performance than the original algorithm of PSO and Constriction PSO.
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