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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
HVAC system optimization—in-building section
TL;DR: In this article, an adaptive neuro-fuzzy inference system (ANFIS) is employed to model duct and pipe networks and obtain optimal differential pressure (DP) set points based on limited sensor information.
Journal ArticleDOI
Scheduling Space–Ground Communications for the Air Force Satellite Control Network
TL;DR: The first coupled formal and empirical analysis of the Satellite Range Scheduling application is presented, showing that the simplified version of the problem is equivalent to a well-known machine scheduling problem and it is proved that Satelliterange Scheduling is NP-complete.
Journal ArticleDOI
Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications
TL;DR: In this paper, a bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed to solve optimization problems, which simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature.
Book ChapterDOI
Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
TL;DR: Important analytical tools are presented, discussed, and applied to well-chosen example functions in the analysis of different variants of evolutionary algorithms on selected functions.
Journal ArticleDOI
Intelligent OLSR Routing Protocol Optimization for VANETs
TL;DR: This paper deals with the optimal parameter setting of the optimized link state routing (OLSR), which is a well-known mobile ad hoc network routing protocol, by defining an optimization problem and finding automatically optimal configurations of this routing protocol.
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