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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.

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Citations
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Sentiment Analysis of Big Data: Methods, Applications, and Open Challenges

TL;DR: Both technical aspect of OMSA (techniques and types) and non-technical aspect in the form of application areas are discussed and these challenges are presented as a future direction for research.
Journal ArticleDOI

Joint optimization of preventive maintenance and inventory control in a production line using simulation

TL;DR: In this paper, an integrated method for preventive maintenance and inventory control of a production line, composed of n machines (n ≥ 1) without intermediate buffers, is proposed, where the machines are subject to failures and an age-dependent preventive maintenance policy is used.
Journal ArticleDOI

Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm

TL;DR: It was concluded that the WOA optimization algorithm could improve the prediction accuracy of the MLP model and may be recommended for accurate wind speed prediction.
Journal ArticleDOI

Decision support for Cybersecurity risk planning

TL;DR: A decision support system for calculating the uncertain risk faced by an organization under cyber attack as a function of uncertain threat rates, countermeasure costs, and impacts on its assets is described.
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Statistical exploratory analysis of genetic algorithms

TL;DR: This methodology addresses the issues of experimental design, blocking, power calculations, and response curve analysis and finds that the effect upon performance of crossover is pre-dominantly linear, while the effect of mutation is predominantly quadratic.
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, +1 more
- 01 Sep 1971 - 
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