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A modified particle swarm optimization for correlated phenomena
Journal article   Peer reviewed

A modified particle swarm optimization for correlated phenomena

A. Arefi and M.R. Haghifam
Applied Soft Computing, Vol.11(8), pp.4640-4654
2011
DOI: https://doi.org/10.1016/j.asoc.2011.07.018
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Abstract

The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

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6 Times Cited - Web of Science

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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.84 Supply Chain & Logistics
4.84.169 Particle Swarm Optimization
Web Of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
ESI research areas
Computer Science
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