Open AccessBook
Genetic Algorithms
About:
The article was published on 2002-01-01 and is currently open access. It has received 17039 citations till now.read more
Citations
More filters
Journal Article
Automatic Test Data Generation for Data Flow Testing Using a Genetic Algorithm
TL;DR: An automatic test data generation technique that uses a genetic algorithm, which is guided by the data flow dependencies in the program, to search for test data to cover its def-use associations, to evaluate the effectiveness of the proposed GA compared to the random testing technique.
Journal ArticleDOI
Three Dimensional Bin Packing Problem with Variable Bin Height
TL;DR: The proposed bin packing algorithm based on packing index is designed to utilize the special problem feature and is used as a building block for a genetic algorithm designed for the 3D-BPP.
Book ChapterDOI
Theoretical Aspects of Evolutionary Algorithms
TL;DR: Some fundamental results on evolutionary algorithms are presented in order to show how theoretical results on randomized search heuristics can be proved and how they contribute to the understanding of evolutionary algorithms.
Journal ArticleDOI
Modeling human behavior in user-adaptive systems: Recent advances using soft computing techniques
TL;DR: This paper examines how soft computing techniques, including fuzzy logic, neural networks, genetic algorithms, fuzzy clustering and neuro-fuzzy systems, have been used, alone or in combination with other machine learning techniques, for user modeling from 1999 to 2004.
A modified firefly algorithm for UCAV path planning
TL;DR: A new modified firefly algorithm (MFA) is proposed to solve the UCAV path planning problem, and a modification is applied to exchange information between top fireflies during the process of the light intensity updating to accelerate the global convergence speed while preserving the strong robustness of the basic FA.
References
More filters
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