Genetic Algorithms and Genetic Programming

Proposal review

Modern Concepts and Practical Applications

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Author(s)
Affenzeller, Michael
Wagner, Stefan
Winkler, Stephan
Beham, Andreas
Language
English
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Abstract
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
URI
https://library.oapen.org/handle/20.500.12657/101465
Keywords
Michael Affenzeller; genetic algorithms; genetic programming; GA Theory; GP Schema theories; time series analysis; population diversity; Heuristic lab; Crossover Operators; Standard GA; Capacitated Vehicle Routing Problem; Building Block Hypothesis; Global Optimal Solution; Schema Theorem; Combinatorial Optimization Problems; GP Population; GP Test; Data Set; Island Model; GA Application; Parallel GAs; Roc Curve; Solution Candidates; VRP; Sequential GA; Melanoma Data Set; Parent Tours; M2 M1; Linear Rank Selection
DOI
10.1201/9781420011326
ISBN
9781420011326, 9781420011326, 9781584886297, 9781138114272, 9780429141973, 9781040044254
OCN
449735109
Publisher
Taylor & Francis
Publisher website
https://taylorandfrancis.com/
Publication date and place
2009
Imprint
Chapman and Hall/CRC
Series
Numerical Insights,
Classification
Computer science
Algorithms and data structures
Information technology: general topics
Data mining
Pages
379
Rights
https://creativecommons.org/licenses/by-nc/4.0/