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13

GECCO
2004
Springer

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Self Adaptation of Operator Rates in Evolutionary Algorithms

13 years 9 months ago

Self Adaptation of Operator Rates in Evolutionary Algorithms

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Abstract. This work introduces a new evolutionary algorithm that adapts the operator probabilities (rates) while evolves the solution of the problem. Each individual encodes its genetic rates. In every generation, each individual is modiﬁed by only one operator that is selected according to the encoded rates. Such rates are updated according to the performance achieved by the oﬀspring (compared to its parent) and a random learning rate. The proposed approach is augmented with a simple transposition operator and tested on a number of benchmark functions.

Jonatan Gomez

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GECCO 2004 | Operator | Operator Probabilities | Simple Transposition Operator |

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Added	01 Jul 2010
Updated	01 Jul 2010
Type	Conference
Year	2004
Where	GECCO
Authors	Jonatan Gomez

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