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» Evolving Crossover Operators for Function Optimization
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CORR
2004
Springer
81views Education» more  CORR 2004»
13 years 7 months ago
Optimizing genetic algorithm strategies for evolving networks
This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best...
Matthew J. Berryman, Andrew Allison, Derek Abbott
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 months ago
Self-adaptive simulated binary crossover for real-parameter optimization
Simulated binary crossover (SBX) is a real-parameter recombination operator which is commonly used in the evolutionary algorithm (EA) literature. The operator involves a parameter...
Kalyanmoy Deb, Karthik Sindhya, Tatsuya Okabe
GECCO
2008
Springer
164views Optimization» more  GECCO 2008»
13 years 8 months ago
Genetic algorithms with local search optimization for protein structure prediction problem
This paper presents a new Genetic Algorithm for Protein Structure Prediction problem in both 2D and 3D hydrophobichydrophilic lattice models, introduced in [1]. Our algorithm evol...
Igor Berenboym, Mireille Avigal
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
14 years 20 days ago
A Survey on Chromosomal Structures and Operators for Exploiting Topological Linkages of Genes
Abstract. The building block hypothesis implies that the epistatic property of a given problem must be connected well to the linkage property of the employed representation and cro...
Dong-il Seo, Byung Ro Moon
GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning building block structure from crossover failure
In the classical binary genetic algorithm, although crossover within a building block (BB) does not always cause a decrease in fitness, any decrease in fitness results from the ...
Zhenhua Li, Erik D. Goodman