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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
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Hybridizing a genetic algorithm with an artificial immune system for global optimization
TL;DR: The results indicate that the proposed algorithm to handle constraints of all types in a genetic algorithm used for global optimization is highly competitive with respect to penalty-based techniques and withrespect to other constraint-handling techniques which are considerably more complex to implement.
Journal ArticleDOI
A probabilistic analysis of a simplified biogeography-based optimization algorithm
TL;DR: A simplified version of BBO is presented and an approximate analysis of the BBO population using probability theory is performed to provide approximate values for the expected number of generations before the population's best solution improves, and the expected amount of improvement.
Journal ArticleDOI
Genetic Algorithms for Project Management
TL;DR: This research has developed a new technique based on genetic algorithms (GA) that automatically determines, using a programmable goal function, a near-optimal allocation of resources and resulting schedule that satisfies a given task structure and resource pool.
Journal ArticleDOI
A novel Black Widow Optimization algorithm for multilevel thresholding image segmentation
TL;DR: The novel meta-heuristic algorithm called Black Widow Optimization (BWO) is introduced to find the best threshold configuration using Otsu or Kapur as objective function and is found to be most promising for multi-level image segmentation problem over other segmentation approaches that are currently used in the literature.
Journal ArticleDOI
System identification of PEM fuel cells using an improved Elman neural network and a new hybrid optimization algorithm
Dongmin Yu,Dongmin Yu,Yong Wang,Yong Wang,Huanan Liu,Huanan Liu,Kittisak Jermsittiparsert,Navid Razmjooy +7 more
TL;DR: An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.
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