Results 251 to 260 of about 538,821 (309)

The Proportional Genetic Algorithm: Gene Expression in a Genetic Algorithm

Genetic Programming and Evolvable Machines, 2002
Summary: We introduce a genetic algorithm (GA) with a new representation method which we call the proportional GA (PGA). The PGA is a multi-character GA that relies on the existence or non-existence of genes to determine the information that is expressed.
Wu, Annie S., Garibay, Ivan
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Isomorphisms of genetic algorithms

Artificial Intelligence, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Battle, David L., Vose, Michael D.
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Genetic clustering algorithms

European Journal of Operational Research, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chiou, Yu-Chiun, Lan, Lawrence W.
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Genetic algorithms and evolution

Journal of Theoretical Biology, 1990
The genetic algorithm (GA) as developed by Holland (1975, Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press) is an optimization technique based on natural selection. We use a modified version of this technique to investigate which aspects of natural selection make it an efficient search procedure.
B H, Sumida, A I, Houston, J M, McNamara, W D, Hamilton   +3 more
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Genetic algorithms in chemistry

Journal of Chromatography A, 2007
Genetic algorithms (GAs) are a quite recent technique of optimization, whose basic concept is mimicking the evolution of a species, according to the Darwinian theory of the "survival of the fittest." The application of genetic algorithms to complex problems usually produces much better results than those obtained by the standard techniques.
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Genetic algorithms in chemometrics

Journal of Chemometrics, 2012
This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity ...
A. Niazi, LEARDI, RICCARDO
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Optimization of Genetic Algorithms by Genetic Algorithms

1993
This paper presents an approach to determine the optimal Genetic Algorithm (GA), i.e. the most preferable type of genetic operators and their parameter settings, for a given problem. The basic idea is to consider the search for the best GA as an optimization problem and use another GA to solve it. As a consequence, a primary GA operates on a population
Bernd Freisleben, Michael Härtfelder
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Putting More Genetics into Genetic Algorithms

Evolutionary Computation, 1998
The majority of current genetic algorithms (GAs), while inspired by natural evolutionary systems, are seldom viewed as biologically plausible models. This is not a criticism of GAs, but rather a reflection of choices made regarding the level of abstraction at which biological mechanisms are modeled, and a reflection of the more engineering-oriented ...
D S, Burke, K A, De Jong, J J, Grefenstette, C L, Ramsey, A S, Wu   +4 more
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