SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS

Ghodrat Moghadampour

2011

Abstract

Evolutionary algorithms are affected by more parameters than optimization methods typically. This is at the same time a source of their robustness as well as a source of frustration in designing them. Adaptation can be used not only for finding solutions to a given problem, but also for tuning genetic algorithms to the particular problem. Adaptation can be applied to problems as well as to evolutionary processes. In the first case adaptation modifies some components of genetic algorithms to provide an appropriate form of the algorithm, which meets the nature of the given problem. These components could be any of representation, crossover, mutation and selection. In the second case, adaptation suggests a way to tune the parameters of the changing configuration of genetic algorithms while solving the problem. In this paper two new self-adaptive mutation operators; integer and decimal mutation are proposed for implementing efficient mutation in the evolutionary process of genetic algorithm for function optimization. Experimentation with 27 test cases and 1350 runs proved the efficiency of these operators in solving optimization problems.

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Paper Citation


in Harvard Style

Moghadampour G. (2011). SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 184-191. DOI: 10.5220/0003494401840191


in Harvard Style

Moghadampour G. (2011). SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 184-191. DOI: 10.5220/0003494401840191


in Bibtex Style

@conference{iceis11,
author={Ghodrat Moghadampour},
title={SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={184-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003494401840191},
isbn={978-989-8425-54-6},
}


in Bibtex Style

@conference{iceis11,
author={Ghodrat Moghadampour},
title={SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={184-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003494401840191},
isbn={978-989-8425-54-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS
SN - 978-989-8425-54-6
AU - Moghadampour G.
PY - 2011
SP - 184
EP - 191
DO - 10.5220/0003494401840191


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - SELF-ADAPTIVE INTEGER AND DECIMAL MUTATION OPERATORS FOR GENETIC ALGORITHMS
SN - 978-989-8425-54-6
AU - Moghadampour G.
PY - 2011
SP - 184
EP - 191
DO - 10.5220/0003494401840191