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» Combining mutation operators in evolutionary programming
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CEC
2010
IEEE
13 years 5 months ago
Implementing an intuitive mutation operator for interactive evolutionary 3D design
Abstract— Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been described as a key element in Evolutionary Computation. Grammatical Evolutio...
Jonathan Byrne, James McDermott, Edgar Galvá...
CEC
2009
IEEE
14 years 2 days ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
CEC
2007
IEEE
13 years 11 months ago
Self-adaptation of mutation distribution in evolutionary algorithms
— This paper proposes a self-adaptation method to control not only the mutation strength parameter, but also the mutation distribution for evolutionary algorithms. For this purpo...
Renato Tinós, Shengxiang Yang
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
13 years 10 months ago
The Principle of Maximum Entropy-Based Two-Phase Optimization of Fuzzy Controller by Evolutionary Programming
In this paper, a two-phase evolutionary optimization scheme is proposed for obtaining optimal structure of fuzzy control rules and their associated weights, using evolutionary prog...
Chi-Ho Lee, Ming Yuchi, Hyun Myung, Jong-Hwan Kim
ICALP
2003
Springer
13 years 10 months ago
Analysis of a Simple Evolutionary Algorithm for Minimization in Euclidean Spaces
Although evolutionary algorithms (EAs) are widely used in practical optimization, their theoretical analysis is still in its infancy. Up to now results on the (expected) runtime ar...
Jens Jägersküpper