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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

ISBN: 978-989-758-122-9

Keyword(s): Genetic Algorithm, Evolution Strategy, Cuckoo Search, Differential Evolution, Particle Swarm Optimization, Benchmark Comparison, Unconstrained Optimization.

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 provide a systematic comparison of the following population-based optimization techniques: Genetic Algorithm (GA), Evolution Strategy (ES), Cuckoo Search (CS), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The considered techniques have been implemented and evaluated on a set of 67 multivariate functions. We carefully selected the tested optimization functions which have different features and gave exactly the same number of objective function evaluations for all of the algorithms. This study has revealed that the DE algorithm is preferable in the majority of cases of the tested functions. The results of numerical evaluations and parameter optimization are presented in this paper.

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Paper citation in several formats:
Sidorov, M.; Semenkin, E. and Minker, W. (2015). Unconstrained Global Optimization: A Benchmark Comparison of Population-based Algorithms.In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 230-237. DOI: 10.5220/0005548002300237

@conference{icinco15,
author={Maxim Sidorov. and Eugene Semenkin. and Wolfgang Minker.},
title={Unconstrained Global Optimization: A Benchmark Comparison of Population-based Algorithms},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={230-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005548002300237},
isbn={978-989-758-122-9},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Unconstrained Global Optimization: A Benchmark Comparison of Population-based Algorithms
SN - 978-989-758-122-9
AU - Sidorov, M.
AU - Semenkin, E.
AU - Minker, W.
PY - 2015
SP - 230
EP - 237
DO - 10.5220/0005548002300237

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