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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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Book ChapterDOI
Computational Intelligence: An Introduction
TL;DR: The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.
Journal ArticleDOI
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Olli Bräysy,Michel Gendreau +1 more
TL;DR: This paper surveys the research on the metaheuristics for the Vehicle Routing Problem with Time Windows and describes basic features of each method, and experimental results for Solomon's benchmark test problems are presented and analyzed.
Journal ArticleDOI
A Taxonomy of Hybrid Metaheuristics
TL;DR: A taxonomy of hybrid metaheuristics is presented in an attempt to provide a common terminology and classification mechanisms and is also applicable to most types of heuristics and exact optimization algorithms.
Journal ArticleDOI
Methods of integrating data to uncover genotype–phenotype interactions
TL;DR: The emerging approaches for data integration — including meta-dimensional and multi-staged analyses — which aim to deepen the understanding of the role of genetics and genomics in complex outcomes are explored.
PatentDOI
Achromatic Metasurface Optical Components by Dispersive Phase Compensation
Francesco Aieta,Mikhail A. Kats,Patrice Genevet,Federico Capasso,Mohammadreza Khorasaninejad +4 more
TL;DR: It is shown that chromatic dispersion, or color dependence, can be compensated for by the judicious design of the surface, and an engineered wavelength-dependent phase shift imparted by a metasurface is demonstrated.
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