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Genetic Algorithms
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The article was published on 2002-01-01 and is currently open access. It has received 17039 citations till now.read more
Citations
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Closed-Loop Turbulence Control: Progress and Challenges
Steven L. Brunton,Bernd R. Noack +1 more
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Emperor penguin optimizer: A bio-inspired algorithm for engineering problems
Gaurav Dhiman,Vijay Kumar +1 more
TL;DR: A novel optimization algorithm, called Emperor Penguin Optimizer (EPO), which mimics the huddling behavior of emperor penguins, which is compared with eight state-of-the-art optimization algorithms.
Journal ArticleDOI
Chemical-Reaction-Inspired Metaheuristic for Optimization
Albert Y. S. Lam,Victor O. K. Li +1 more
TL;DR: This work proposes a new metaheuristic, called chemical reaction optimization (CRO), which mimics the interactions of molecules in a chemical reaction to reach a low energy stable state and can outperform all other metaheuristics when matched to the right problem type.
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Ant colony optimization for routing and load-balancing: survey and new directions
Kwang Mong Sim,Weng Hong Sun +1 more
TL;DR: In this survey, the problem-solving paradigm of ACO is explicated and compared to traditional routing algorithms along the issues of routing information, routing overhead and adaptivity.
Journal ArticleDOI
Chimp optimization algorithm
TL;DR: A novel metaheuristic algorithm inspired by the individual intelligence and sexual motivation of chimps in their group hunting, which is different from the other social predators, is proposed, which indicates that the ChOA outperforms the other benchmark optimization algorithms.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
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An Introduction to Genetic Algorithms.
TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Book
Handbook of Genetic Algorithms
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
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An Introduction to Population Genetics Theory
James F. Crow,Motoo Kimura +1 more
TL;DR: An introduction to population genetics theory, An introduction to Population Genetics Theory, Population Genetics theory, Population genetics theory as discussed by the authors, Population genetics, population genetics, and population genetics theories, Population Genetic Theory