Genetic algorithms in chemistry

https://doi.org/10.1016/0169-7439(93)80028-GGet rights and content

Abstract

Genetic algorithms (GAs), a set of optimisation techniques, are so called after their similarity to evolutionary processes in nature. The algorithm's equivalents of genes and chromosomes are the unknown parameters of the problem and these may be mated and mutated to give better solutions. The major strengths of GAs, namely the ability to search a large parameter space with no initial guesses per se, no derivatives of the objective function and to cope with local minima, make it a candidate method for several areas of chemistry. Chemical problems that have been tackled by GAs are described and suggestions for new applications are made. Subroutines in object-oriented Pascal are given to set up a simple GA.

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