Evolutionary Computation algorithms are inspired by biological evolution. They are based on a random population, and they work with trial and error. Evolutionary Computation is a family of algorithms for finding the global optimum. They are based on a random population, and they work with trial and error. The general idea of these algorithms is that when there is a population available, each population member has some qualities, and these qualities can be good or bad. If one of the population members has more bad qualities than others, the chance for survival becomes less than others for that member, and the possibility of making the next generation will be less than the others for that member. With this concept, the population will become better and better each generation because a better part of the generation will make the next generation.
Shree2244/Evolutionary-Computing
Evolutionary Computation algorithms are inspired by biological evolution. They are based on a random population, and they work with trial and error.
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