Evolutionary programming

Evolutionary programming (EP), created by Lawrence J. Fogel in 1960, is a stochastic optimization strategy similar to genetic algorithms and evolution 

Initially, the variables are vectors from a bounded subspace of R . Afterwards, the search domain is extended to the whole space. The Meta-evolutionary programming approach also incorporates strategy parameters (standard deviations) in this representation. 

The fitness values are obtained from objective function values by scaling to positive values and possibly by imposing a random alteration. 

No recombination operator combining features of different individuals is used with EP. In EP, individuals are viewed as species, and distinct species do not recombine. 

Each individual is replicated into a new population. Each offspring is mutated according to a distribution of mutation types, from minor to extreme. The severity of mutations is often reduced as the global optimum is 

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GeUiaar D K, G M Verkhivker, P A Rejto, C J Sherman, D B Fogel, L J Fogel and S T Freer 1995 Molecular Recognition of the Inhibitor AG-1343 by HFV-l Protease Conformationally FlexibL Docking by Evolutionary Programming. Chemistry and Biology 2 317-324. 

BT Luke. Evolutionary programming applied to the development of quantitative structure-activity relationships and quantitative structure-property relationships. J Chem Inf Comput Sci 34(6) I279-1287, 1994. 

Fogel, D. B. A Comparison of Evolutionary Programming and Genetic Algorithms on Selected Constrained Optimization Problems. Simulation 64 397-404 (1995). 

Greeff, D. J. and C. Aldrich. Empirical Modelling of Chemical Process Systems with Evolutionary Programming Comput Chem Eng 22 995-1005 (1998). 

Rejto, P.A., Sherman, C.J., and Fogel, D.B. Molecular recognition of the inhibitor AG-1343 by HlV-1 protease conformationally flexible docking by evolutionary programming. Chem. Biol. 1995, 2, 317-324. 

Gehlhaar, D. K., Bouzida, D., Rejto, P. A. (1998) Fully automated and rapid flexible docking of inhibitors covalently bound to serine proteases. Proceedings of the 7th International Conference on Evolutionary Programming, MIT Press, Cambridge, MA., pp. 449-461. 

Back, T. Evolutionary Algorithms in Theory and Practice Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, New York,... 

Back T (1996) Evolutionary Algorithms in theory and practice evolution strategies, evolutionary programming, genetic algorithms. Oxford University Press, Oxford... 

So and Karplus [51] have developed a hybrid method that combines a GA for descriptor selection with an artificial neural network for model building. They found improved models for the Selwood data set when compared with the GFA and evolutionary programming methods, with the success being attributed to the ability of the neural network to select nonlinear descriptors. 

We have pursued a plug-and-play strategy with two different energy functions, a molecular mechanics AMBER force field [131,132] and a simplified energy function, along with two different sampling techniques, evolutionary programming [91] and Monte Carlo simulations [118,119,127,128]. 

Luke, B.T. (1994). Evolutionary Programming Applied to the Development of Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships. J.Chem. Inf.Comput.Sci., 34,1279-1287. 

Gehlhaar DK, Verkhivker GM, Rejto PA, Sherman CJ, Fogel DB, Fogel LJ, Freer ST. Molecular recognition of the inhibitor Ag-1343 by Hiv-1 protease—conformationally flexible docking by evolutionary programming. Chem Biol 1995 2 317-324. 

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