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Authors: Maxim Sidorov 1 ; Eugene Semenkin 2 and Wolfgang Minker 1

Affiliations: 1 Ulm University, Germany ; 2 Siberian State Aerospace University, Russian Federation

Keyword(s): Genetic Algorithm, Evolution Strategy, Particle Swarm Optimization, Island and Co-evolution Cooperation Models.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Optimization Algorithms ; Soft Computing

Abstract: In this paper we present multi-agent cooperative algorithms of global optimization based on a genetic algorithm, an evolution strategy and particle swarm optimization. Island and co-evolution approaches have been selected as a main scheme of cooperation. The proposed techniques have been implemented and evaluated on a set of 22 multivariate functions. We assert that the proposed techniques could achieve much higher results in terms of reliability and speed criteria than the performance of corresponding conventional algorithms (without cooperative schemes) with average parameters on 18 functions from the 22 selected for the evaluation procedure. Such advantages are much more observable with increasing dimensionality of functions. Furthermore, the performance of the suggested algorithms was even higher than the performance of conventional algorithms with the best parameters for 5 functions.

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Paper citation in several formats:
Sidorov, M., Semenkin, E. and Minker, W. (2014). Multi-agent Cooperative Algorithms of Global Optimization. In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-039-0; ISSN 2184-2809, SciTePress, pages 259-265. DOI: 10.5220/0005049402590265

@conference{icinco14,
author={Maxim Sidorov and Eugene Semenkin and Wolfgang Minker},
title={Multi-agent Cooperative Algorithms of Global Optimization},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2014},
pages={259-265},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005049402590265},
isbn={978-989-758-039-0},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Multi-agent Cooperative Algorithms of Global Optimization
SN - 978-989-758-039-0
IS - 2184-2809
AU - Sidorov, M.
AU - Semenkin, E.
AU - Minker, W.
PY - 2014
SP - 259
EP - 265
DO - 10.5220/0005049402590265
PB - SciTePress

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