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https://github.com/saranshmanu/genetic-optimisation-algorithm

Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection.
https://github.com/saranshmanu/genetic-optimisation-algorithm

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Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection.

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# Genetic-Optimisation-Algorithm

Genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection. John Holland introduced Genetic Algorithm (GA) in 1960 based on the concept of the Darwin’s theory of evolution; afterwards, his student Goldberg extended GA in the 1989.