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Authors: Carlos M. Fernandes 1 ; Juan Julán Merelo 1 and Agostinho C. Rosa 2

Affiliations: 1 University of Granada, Spain ; 2 Technical University of Lisbon, Portugal

ISBN: 978-989-8425-31-7

Keyword(s): Genetic algorithms, Dissortative mating, Dynamic optimization problems.

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

Abstract: This paper investigates the effects of modifying the Adaptive Dissortative Mating Genetic Algorithm (ADMGA) replacement strategy on the performance of the algorithm in dynamic problems. ADMGA is a variation of the standard GA with a mating restriction based on the genotypic similarity of the individuals. Dissimilar individuals mate more often than expected by chance and, as a result, genetic diversity throughout the run is maintained at a higher level. ADMGA was previously tested in dynamic optimization problems with promising results: the algorithm shows to outperform standard GAs and state-of-the-art approaches on several problems and dynamics. However, the performance of the algorithm degrades when the frequency of changes increases. Due to the premises under which ADMGA was tested, it has been argued that the replacement strategy that emerges from the algorithm’s dissortative mating strategy may be harming the performance in such situations. This study proposes alternative replace ment schemes with the objective of improving ADMGA’s performance on fast changing environments (without damaging the performance on slower ones). The strategies maintain the simplicity of the algorithm, i.e., the parameter set is not increased. The replacement schemes were tested in dynamic environments based on stationary functions with different characteristics, showing to improve standard ADMGA’s performance in fast dynamic problems. (More)

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Paper citation in several formats:
Fernandes, C.; Merelo, J. and Rosa, A. (2010). INVESTIGATING REPLACEMENT STRATEGIES FOR THE ADAPTIVE DISSORTATIVE MATING GENETIC ALGORITHM.In Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010) ISBN 978-989-8425-31-7, pages 104-113. DOI: 10.5220/0003087001040113

@conference{icec10,
author={Carlos M. Fernandes. and Juan Julán Merelo. and Agostinho C. Rosa.},
title={INVESTIGATING REPLACEMENT STRATEGIES FOR THE ADAPTIVE DISSORTATIVE MATING GENETIC ALGORITHM},
booktitle={Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)},
year={2010},
pages={104-113},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003087001040113},
isbn={978-989-8425-31-7},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)
TI - INVESTIGATING REPLACEMENT STRATEGIES FOR THE ADAPTIVE DISSORTATIVE MATING GENETIC ALGORITHM
SN - 978-989-8425-31-7
AU - Fernandes, C.
AU - Merelo, J.
AU - Rosa, A.
PY - 2010
SP - 104
EP - 113
DO - 10.5220/0003087001040113

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