A Novel Genetic Algorithm For Biomolecular Interaction Studies
Abstract
The examination of recent developments in genetic algorithms is covered in this work. The genetic algorithms chosen for analysis are those that the scientific community finds to be of considerable interest. The fresh and demanding researchers will benefit from this review's ability to provide a broader perspective on genetic algorithms. The popular algorithms' benefits and drawbacks, as well as how they are implemented, are presented. In order to aid novice researchers, the genetic operators and their applications are discussed. There is coverage of the various study fields related to genetic algorithms. Future directions for research in the fields of genetic operators, fitness metrics, and hybrid algorithms are covered. This organized review will be beneficial for graduate teaching and research.
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