Materials Science and Nanotechnology

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Materials Science and Nanotechnology 44 7897 074717

Evolutionary Algorithm New Open Access Journals

Evolutionary algorithms are a heuristic-based attack to solving problems that cannot be well solved in polynomial time, such as classically NP-Hard problems, and anything else that would take far too long to thoroughly process. When used on their own, they are typically applied to combinatorial problems; however, genetic algorithms are often used in tandem with other methods, acting as a quick way to find a somewhat optimal starting place for some other algorithm to work off of. The premise of an evolutionary algorithm is quite simple given that you are familiar with the process of natural selection. Evolutionary algorithms contain four overall steps: initialization, selection, genetic operators, and termination. These steps each check, roughly, to a special facet of natural option, and supply easy ways to modularize implementations of this algorithm category.

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