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Authors: Carlos Eduardo Klein 1 ; Emerson Hochsteiner de Vasconcelos Segundo 1 ; Viviana Cocco Mariani 2 and Leandro dos Santos Coelho 2

Affiliations: 1 Pontifical Catholic University of Parana, Brazil ; 2 Pontifical Catholic University of Parana and Federal University of Parana (UFPR), Brazil

ISBN: 978-989-758-052-9

Keyword(s): Metaheuristics, Swarm Intelligence, Flower Pollination Algorithm, Electromagnetic Optimization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Soft Computing ; Swarm/Collective Intelligence

Abstract: It is difficult to use the deterministic mathematical tools such as a gradient method to solve global optimization problems. Flower pollination algorithm (FPA) is a new nature-inspired algorithm of the swarm intelligence field to global optimization applications, based on the characteristics of flowering plants. To enhance the performance of the standard FPA, an enhanced FPA (EFPA) approach based on beta probability distribution was proposed in this paper. In order to verify the performance of the proposed EFPA, five benchmark functions are chosen from the literature as the test suit. Furthermore, tests using Loney’s solenoid benchmark, a classical problem in the electromagnetics area, are realized to evaluate the effectiveness of the FPA and the proposed EFPA. Simulation results and comparisons with the FPA demonstrated that the performance of the EFPA approach is promising in electromagnetics optimization.

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Paper citation in several formats:
Klein, C.; Segundo, E.; Mariani, V. and Coelho, L. (2014). Enhanced Flower Pollination Approach Applied to Electromagnetic Optimization.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014) ISBN 978-989-758-052-9, pages 223-227. DOI: 10.5220/0005074502230227

@conference{ecta14,
author={Carlos Eduardo Klein. and Emerson Hochsteiner de Vasconcelos Segundo. and Viviana Cocco Mariani. and Leandro dos Santos Coelho.},
title={Enhanced Flower Pollination Approach Applied to Electromagnetic Optimization},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)},
year={2014},
pages={223-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005074502230227},
isbn={978-989-758-052-9},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)
TI - Enhanced Flower Pollination Approach Applied to Electromagnetic Optimization
SN - 978-989-758-052-9
AU - Klein, C.
AU - Segundo, E.
AU - Mariani, V.
AU - Coelho, L.
PY - 2014
SP - 223
EP - 227
DO - 10.5220/0005074502230227

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