Foundations of Global Genetic Optimization

Foundations of Global Genetic Optimization
Author :
Publisher : Springer
Total Pages : 227
Release :
ISBN-10 : 9783540731924
ISBN-13 : 354073192X
Rating : 4/5 (92X Downloads)

Book Synopsis Foundations of Global Genetic Optimization by : Robert Schaefer

Download or read book Foundations of Global Genetic Optimization written by Robert Schaefer and published by Springer. This book was released on 2007-07-07 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms today constitute a family of e?ective global optimization methods used to solve di?cult real-life problems which arise in science and technology. Despite their computational complexity, they have the ability to explore huge data sets and allow us to study exceptionally problematic cases in which the objective functions are irregular and multimodal, and where information about the extrema location is unobtainable in other ways. Theybelongtotheclassofiterativestochasticoptimizationstrategiesthat, during each step, produce and evaluate the set of admissible points from the search domain, called the random sample or population. As opposed to the Monte Carlo strategies, in which the population is sampled according to the uniform probability distribution over the search domain, genetic algorithms modify the probability distribution at each step. Mechanisms which adopt sampling probability distribution are transposed from biology. They are based mainly on genetic code mutation and crossover, as well as on selection among living individuals. Such mechanisms have been testedbysolvingmultimodalproblemsinnature,whichiscon?rmedinpart- ular by the many species of animals and plants that are well ?tted to di?erent ecological niches. They direct the search process, making it more e?ective than a completely random one (search with a uniform sampling distribution). Moreover,well-tunedgenetic-basedoperationsdonotdecreasetheexploration ability of the whole admissible set, which is vital in the global optimization process. The features described above allow us to regard genetic algorithms as a new class of arti?cial intelligence methods which introduce heuristics, well tested in other ?elds, to the classical scheme of stochastic global search.


Foundations of Global Genetic Optimization Related Books

Foundations of Global Genetic Optimization
Language: en
Pages: 227
Authors: Robert Schaefer
Categories: Technology & Engineering
Type: BOOK - Published: 2007-07-07 - Publisher: Springer

GET EBOOK

Genetic algorithms today constitute a family of e?ective global optimization methods used to solve di?cult real-life problems which arise in science and technol
Genetic Algorithms and Engineering Optimization
Language: en
Pages: 520
Authors: Mitsuo Gen
Categories: Technology & Engineering
Type: BOOK - Published: 1999-12-28 - Publisher: John Wiley & Sons

GET EBOOK

Im Mittelpunkt dieses Buches steht eines der wichtigsten Optimierungsverfahren der industriellen Ingenieurtechnik: Mit Hilfe genetischer Algorithmen lassen sich
Genetic Algorithm Essentials
Language: en
Pages: 94
Authors: Oliver Kramer
Categories: Technology & Engineering
Type: BOOK - Published: 2017-01-07 - Publisher: Springer

GET EBOOK

This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand a
Genetic Algorithms and Fuzzy Multiobjective Optimization
Language: en
Pages: 306
Authors: Masatoshi Sakawa
Categories: Business & Economics
Type: BOOK - Published: 2002 - Publisher: Springer Science & Business Media

GET EBOOK

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been publi
Genetic Algorithms in Search, Optimization, and Machine Learning
Language: en
Pages: 436
Authors: David Edward Goldberg
Categories: Computers
Type: BOOK - Published: 1989 - Publisher: Addison-Wesley Professional

GET EBOOK

A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applic