Genetic algorithms are useful for solving problems having solutions
representable as strings (hence the name Genetic Algorithm - the programming
model is based on DNA). In terms of practical value, genetic algorithms are
useful for solving problems in which the solutions are difficult to find by
following a specific algorithm designed to solve the problem (using genetic
algorithms in place of predesigned algorithms such as Djikstra's algorithm for
path finding just wouldn't make sense). It functions as a sort of systematized
brute force approach. Problems genetic algorithms are valuable for solving
include scheduling problems, constraint satisfaction problems, and other
problems that require searching a large number of possibilities. Genetic
algorithms can be applied to protein folding or even tuning Linux kernel performance. more...
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