Towards Finding an Effective Way of Discrete Problems Solving: The Particle Swarm Optimization, Genetic Algorithm and Linkage Learning Techniques Hybrydization

Bartosz Andrzej Fidrysiak, Michal Przewozniczek

2015

Abstract

Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are well known optimization tools. PSO advantage is its capability for fast convergence to the promising solutions. On the other hand GAs are able to process schemata thanks to the use of crossover operator. However, both methods have also their drawbacks – PSO may fall into the trap of preconvergence, while GA capability of fast finding locally optimal (or close to optimal) solutions seems low when compared to PSO. Relatively new, important research direction in the field of Evolutionary Algorithms is linkage learning. The linkage learning methods gather the information about possible gene dependencies and use it to improve their effectiveness. Recently, the linkage learning evolutionary methods were shown to be effective tools to solve both: theoretical and practical problems. Therefore, this paper proposes a PSO and GA hybrid, improved by the linkage learning mechanisms, dedicated to solve binary problems. The proposed method tries to combine the GA schema processing ability, linkage information processing and uses fast PSO convergence to quickly improve the quality of already known solutions.

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Paper Citation


in Harvard Style

Andrzej Fidrysiak B. and Przewozniczek M. (2015). Towards Finding an Effective Way of Discrete Problems Solving: The Particle Swarm Optimization, Genetic Algorithm and Linkage Learning Techniques Hybrydization . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 228-236. DOI: 10.5220/0005596602280236


in Bibtex Style

@conference{ecta15,
author={Bartosz Andrzej Fidrysiak and Michal Przewozniczek},
title={Towards Finding an Effective Way of Discrete Problems Solving: The Particle Swarm Optimization, Genetic Algorithm and Linkage Learning Techniques Hybrydization},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={228-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005596602280236},
isbn={978-989-758-157-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - Towards Finding an Effective Way of Discrete Problems Solving: The Particle Swarm Optimization, Genetic Algorithm and Linkage Learning Techniques Hybrydization
SN - 978-989-758-157-1
AU - Andrzej Fidrysiak B.
AU - Przewozniczek M.
PY - 2015
SP - 228
EP - 236
DO - 10.5220/0005596602280236