<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Since canonical PSO method has many disadvantages which do not allow to effectively reach the global minima of various functions it needs to be improved. The article refers to a novel Multi-Epoch Particle Swarm Optimization (ME-PSO) technique which has been developed by authors. ME-PSO algorithm is based on reinitializing of the stagnant swarm with low exploration efficiency. This approach provides a high rate of global best changing. As a result ME-PSO has great possibility of finding good local (or even global) optimum and does not trap in bad local optimum. In order to prove the advantages of the ME-PSO technique numerical experiments have been carried out with ten uni- and multimodal benchmark functions. Analysis of the obtained results convincingly showed significant superiority of ME-PSO over PSO and IA-PSO algorithms. It has been set that canonical PSO is a special case of ME-PSO.</p></abstract>

Since canonical PSO method has many disadvantages which do not allow to effectively reach the global minima of various functions it needs to be improved. The article refers to a novel Multi-Epoch Particle Swarm Optimization (ME-PSO) technique which has been developed by authors. ME-PSO algorithm is based on reinitializing of the stagnant swarm with low exploration efficiency. This approach provides a high rate of global best changing. As a result ME-PSO has great possibility of finding good local (or even global) optimum and does not trap in bad local optimum. In order to prove the advantages of the ME-PSO technique numerical experiments have been carried out with ten uni- and multimodal benchmark functions. Analysis of the obtained results convincingly showed significant superiority of ME-PSO over PSO and IA-PSO algorithms. It has been set that canonical PSO is a special case of ME-PSO.

A Novel Multi-Epoch Particle Swarm Optimization Technique

Department of Machines and Equipment Design

National University of Life and Environmental Sciences of Ukraine

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A Novel Multi-Epoch Particle Swarm Optimization Technique"}

Since canonical PSO method has many disadvantages which do not allow to effectively reach the global minima of various functions it needs to be improved. The...

A Novel Multi-Epoch Particle Swarm Optimization Technique

Online veröffentlicht: 19. Sept. 2018

Seitenbereich: 62 - 74

Eingereicht: 22. Juni 2018

Akzeptiert: 17. Aug. 2018

DOI: https://doi.org/10.2478/cait-2018-0039

Schlüsselwörter
Particle swarm optimization, multi-epoch technique, Benchmark functions, convergence

© 2018 Romasevych Yuriy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Novel Multi-Epoch Particle Swarm Optimization Technique

Online veröffentlicht: 19. Sept. 2018

Seitenbereich: 62 - 74

Eingereicht: 22. Juni 2018

Akzeptiert: 17. Aug. 2018

DOI: https://doi.org/10.2478/cait-2018-0039

SchlüsselwörterParticle swarm optimization, multi-epoch technique, Benchmark functions, convergence

© 2018 Romasevych Yuriy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Particle swarm optimization, multi-epoch technique, Benchmark functions, convergence