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GECCO
1999
Springer
145views Optimization» more  GECCO 1999»
14 years 1 months ago
Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem
This paper explores the use of growth processes, or embryogenies, to map genotypes to phenotypes within evolutionary systems. Following a summary of the significant features of em...
Peter J. Bentley, Sanjeev Kumar
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 3 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
GECCO
2008
Springer
119views Optimization» more  GECCO 2008»
13 years 10 months ago
Evolutionary synthesis of low-sensitivity equalizers using adjacency matrix representation
An evolutionary synthesis method to design low-sensitivity IIR filters with linear phase in the passband is presented. The method uses a chromosome coding scheme based on the grap...
Leonardo Bruno de Sá, Antonio Carneiro Mesq...
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 10 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
14 years 3 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...