Description: Introduction to Genetic Algorithms by S.N. Sivanandam, S.N. Deepa Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather than over organisms. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description Theoriginofevolutionaryalgorithmswasanattempttomimicsomeoftheprocesses taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather than over organisms. The former are organic tools encoding the structure of a living being, i.e., a cr- ture is "built" decoding a set of chromosomes. • Natural selection is the mechanism that relates chromosomes with the ef ciency of the entity they represent, thus allowing that ef cient organism which is we- adapted to the environment to reproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage. There exists a large number of reproductive mechanisms in Nature. Most common ones are mutation (that causes the chromosomes of offspring to be different to those of the parents) and recombination (that combines the chromosomes of the parents to produce the offspring). Based upon the features above, the three mentioned models of evolutionary c- puting were independently (and almost simultaneously) developed. Notes The basic concept of Genetic Algorithms is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book features basic concepts, several applications of genetic algorithms and solved genetic problems using MATLAB software and C/C++. It is written for a wide range of readers who wish to learn the basic concepts of genetic algorithms with a minimal effort. Back Cover Genetic Algorithms are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. The basic concept of Genetic Algorithms is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book also explores the different types are Genetic Algorithms available with their importance. Implementation of Genetic Algorithm concept has been performed using the universal language C/C++ and the discussion also extends to Genetic Algorithm MATLAB Toolbox. Few Genetic Algorithm problems are programmed using MATLAB and the simulated results are given for the ready reference of the reader. The applications of Genetic Algorithms in Machine learning, Mechanical Engineering, Electrical Engineering, Civil Engineering, Data Mining, Image Processing, and VLSI are dealt to make the readers understand where the concept can be applied. Table of Contents Evolutionary Computation.- Genetic Algorithms.- Terminologies and Operators of GA.- Advanced Operators and Techniques in Genetic Algorithm.- Classification of Genetic Algorithm.- Genetic Programming.- Genetic Algorithm Optimization Problems.- Genetic Algorithm Implementation Using Matlab.- Genetic Algorithm Optimization in C/C++.- Applications of Genetic Algorithms.- to Particle Swarm Optimization and Ant Colony Optimization. Long Description Theoriginofevolutionaryalgorithmswasanattempttomimicsomeoftheprocesses taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: * Evolution is a process operating over chromosomes rather than over organisms. The former are organic tools encoding the structure of a living being, i.e., a cr- ture is "built" decoding a set of chromosomes. * Natural selection is the mechanism that relates chromosomes with the ef ciency of the entity they represent, thus allowing that ef cient organism which is we- adapted to the environment to reproduce more often than those which are not. * The evolutionary process takes place during the reproduction stage. There exists a large number of reproductive mechanisms in Nature. Most common ones are mutation (that causes the chromosomes of offspring to be different to those of the parents) and recombination (that combines the chromosomes of the parents to produce the offspring). Based upon the features above, the three mentioned models of evolutionary c- puting were independently (and almost simultaneously) developed. Feature Basic introduction to Genetic Algorithms contains basic concepts, several applications of Genetic Algorithms and solved Genetic Problems using MATLAB software and C/C++ Written for a wide range of readers, who wishes to learn the basic concepts of Genetic Algorithms Starters can understand the concepts with a minimal effort Description for Sales People The basic concept of Genetic Algorithms is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book features basic concepts, several applications of genetic algorithms and solved genetic problems using MATLAB software and C/C++. It is written for a wide range of readers who wish to learn the basic concepts of genetic algorithms with a minimal effort. Details ISBN354073189X Author S.N. Deepa Short Title INTRO TO GENETIC ALGORITHMS Pages 442 Language English ISBN-10 354073189X ISBN-13 9783540731894 Media Book Format Hardcover Year 2007 Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K Place of Publication Berlin Country of Publication Germany Affiliation PSG College of Technology Edition 1st DOI 10.1604/9783540731894;10.1007/978-3-540-73190-0 Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Publication Date 2007-10-09 Alternative 9783642092244 DEWEY 620 Audience Undergraduate Illustrations XIX, 442 p. We've got this At The Nile, if you're looking for it, we've got it. 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ISBN-13: 9783540731894
Book Title: Introduction to Genetic Algorithms
Number of Pages: 442 Pages
Language: English
Publication Name: Introduction to Genetic Algorithms
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Publication Year: 2007
Subject: Engineering & Technology, Computer Science
Item Height: 235 mm
Item Weight: 1820 g
Type: Textbook
Author: S. N. Deepa, S.N. Sivanandam
Item Width: 156 mm
Format: Hardcover