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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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Journal ArticleDOI
African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems
TL;DR: The proposed African Vultures Optimization Algorithm (AVOA) is named and simulates African vultures’ foraging and navigation behaviors and indicates the significant superiority of the AVOA algorithm at a 95% confidence interval.
Journal ArticleDOI
Extreme learning machine: algorithm, theory and applications
TL;DR: This paper describes the latest progress of ELM in recent years, including the model and specific applications of ELm, and finally points out the research and development prospects ofELM in the future.
Journal ArticleDOI
Parameter Control in Evolutionary Algorithms: Trends and Challenges
TL;DR: More than a decade after the first extensive overview on parameter control, this work revisits the field and presents a survey of the state-of-the-art.
Book ChapterDOI
Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives
TL;DR: This chapter provides two recent algorithms for evolutionary optimization – well known as particle swarm optimization (PSO) and differential evolution (DE), inspired by biological and sociological motivations and can take care of optimality on rough, discontinuous and multimodal surfaces.
Journal ArticleDOI
Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization
TL;DR: In this article, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems, and a comparison of the proposed algorithm with other algorithms has been made, which shows that FPA is efficient with a good convergence rate.
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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