article
Investigation on adaptive genetic algorithm and metaheuristic methods within stochastic optimisation
International journal of applied research · 2017 · Vol. 3(8) · pp. 835–840
Abstract
In computer science and operations research, a 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. In a genetic algorithm, a population of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem is evolved toward better solutions.
Metaheuristic Optimization Algorithms ResearchCrossoverMetaheuristicGenetic algorithmSelection (genetic algorithm)Quality control and genetic algorithmsMeta-optimizationMathematical optimizationComputer sciencePopulationGenetic representation
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