Comparison Of Particle Swarm And Differential Evolution Optimization Algorithms Considering Various Benchmark Functions

Yıl 2017, Cilt: 20 Sayı: 4, 899 - 905, 20.12.2017

Hasan Özcan

https://doi.org/10.2339/politeknik.369076

Cited By: 1

Öz

This study aims to compare Particle Swarm
Optimization (PSO) and Differential Evolution (DE) methods for various input
parameters. Both optimization methods show high performance in optimization of
any physical system including simple and complex constraints and objectives.
Average and standard values of both methods were evaluated by utilizing 8
benchmark functions and a graphical representation and comparison of
corresponding methods was presented for 50x50 and
100x100 population sizes and dimensionalities. It is concluded that DE and PSO
show the best fitness value for Sum of Different Powers benchmark function for
both number of populations. Approach to the optimum is found to be
faster through the PSO method. Both methods are flexible to be used for simple
and complex engineering problems with high performances with ease of
programming.

Anahtar Kelimeler

Particle swarm, differential evolution, optimization, benchmark function

Kaynakça

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