Materials Science and Nanotechnology

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Materials Science and Nanotechnology 44 7897 074717

Evolutionary Algorithm Research Articles

Evolutionary algorithms are a heuristic-based attack to finding problems that cannot be easily 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 practical to combination problems however, genetic algorithms are often used in tandem with other methods, acting as a quick way to find a somewhat best starting place for another 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. An evolutionary algorithm contains four overall steps: initialization, selection, genetic operators, and termination. These steps each check, roughly, to a special facet of natural selection, and supply easy ways to modularize implementations of this algorithm category.

 

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