Vol. 3, Issue 8, Part K (2017)
Investigation on adaptive genetic algorithm and metaheuristic methods within stochastic optimisation
Investigation on adaptive genetic algorithm and metaheuristic methods within stochastic optimisation
Author(s)
Manjusha Shiradkar, Archana Badgujar and Pavan Dhoke
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.
How to cite this article:
Manjusha Shiradkar, Archana Badgujar, Pavan Dhoke. Investigation on adaptive genetic algorithm and metaheuristic methods within stochastic optimisation. Int J Appl Res 2017;3(8):835-840.