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FOGA
1994
9 years 2 months ago
Predictive Models Using Fitness Distributions of Genetic Operators
An important goal of the theory of genetic algorithms is to build predictive models of how well genetic algorithms are expected to perform, given a representation, a fitness lands...
John J. Grefenstette
AE
2005
Springer
9 years 7 months ago
An Enhanced Genetic Algorithm for Protein Structure Prediction Using the 2D Hydrophobic-Polar Model
This paper presents an enhanced genetic algorithm for the protein structure prediction problem. A new fitness function, that uses the concept of radius of gyration, is proposed. Al...
Heitor S. Lopes, Marcos P. Scapin
GECCO
2008
Springer
164views Optimization» more  GECCO 2008»
9 years 2 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
CORR
2004
Springer
108views Education» more  CORR 2004»
9 years 1 months ago
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
Abstract. This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutatio...
Kumara Sastry, David E. Goldberg, Martin Pelikan
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
9 years 1 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
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