Genetic algorithm principles

Forrest, S. Genetic algorithms principles of natural selection applied to computation. Science 1993, 261,... 

Reeves, C.R. and Rowe, J.E. (2003). Genetic Algorithms Principles and Perspectives, Kluwer, Boston, 332 p. 

A molecular dynamics simulation samples the phase space of a molecule (defined by the position of the atoms and their velocities) by integrating Newton s equations of motion. Because MD accounts for thermal motion, the molecules simulated may possess enough thermal energy to overcome potential barriers, which makes the technique suitable in principle for conformational analysis of especially large molecules. In the case of small molecules, other techniques such as systematic, random. Genetic Algorithm-based, or Monte Carlo searches may be better suited for effectively sampling conformational space. 

Although in principle a genetic algorithm, or other learning algorithm, shoutd f find the true optimum, the search is limited, either by computer limitations in th i case of numerical studies, or by experimental restrictions in the case of laboratory ir experiments. ij]... 

New methods of variable selection include evolutionary methods based on Darwinian principles including Genetic Algorithms and Genetic Programming... 

Other methods such as Genetic Algorithm based on evolution principles, maximum entropy method based on Bayesian theory, and maximum likelihood methods have also been developed. ... 

Devillers, J. ed. (1996). Genetic Algorithms in Molecular Modeling. Principles of QSAR and Drug Design. Vol. 1. Academic Press, London (UK), 327 pp. 

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