Introduction To Evolutionary Algorithms

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Introduction to Evolutionary Computing

Agoston E. Eiben,J.E. Smith
Introduction to Evolutionary Computing Book PDF

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 44,8 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

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Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Introduction to Evolutionary Algorithms

Xinjie Yu,Mitsuo Gen
Introduction to Evolutionary Algorithms Book PDF

Author : Xinjie Yu,Mitsuo Gen
Publisher : Springer Science & Business Media
Page : 422 pages
File Size : 54,7 Mb
Release : 2010-06-10
Category : Computers
ISBN : 9781849961295

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Introduction to Evolutionary Algorithms by Xinjie Yu,Mitsuo Gen Pdf

Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems. The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry. Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such as recommended further reading and ideas for research projects combine to form an accessible and interesting pedagogical approach to this widely used discipline.

An Introduction to Genetic Algorithms

Melanie Mitchell
An Introduction to Genetic Algorithms Book PDF

Author : Melanie Mitchell
Publisher : MIT Press
Page : 226 pages
File Size : 41,9 Mb
Release : 1998-03-02
Category : Computers
ISBN : 0262631857

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An Introduction to Genetic Algorithms by Melanie Mitchell Pdf

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

Introduction to Genetic Algorithms

S.N. Sivanandam,S. N. Deepa
Introduction to Genetic Algorithms Book PDF

Author : S.N. Sivanandam,S. N. Deepa
Publisher : Springer Science & Business Media
Page : 442 pages
File Size : 47,9 Mb
Release : 2007-10-24
Category : Technology & Engineering
ISBN : 9783540731900

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Introduction to Genetic Algorithms by S.N. Sivanandam,S. N. Deepa Pdf

This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Evolutionary Algorithms and Neural Networks

Seyedali Mirjalili
Evolutionary Algorithms and Neural Networks Book PDF

Author : Seyedali Mirjalili
Publisher : Springer
Page : 156 pages
File Size : 40,9 Mb
Release : 2018-06-26
Category : Technology & Engineering
ISBN : 9783319930251

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Evolutionary Algorithms and Neural Networks by Seyedali Mirjalili Pdf

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

A Brief Introduction to Continuous Evolutionary Optimization

Oliver Kramer
A Brief Introduction to Continuous Evolutionary Optimization Book PDF

Author : Oliver Kramer
Publisher : Springer Science & Business Media
Page : 94 pages
File Size : 54,6 Mb
Release : 2013-12-04
Category : Technology & Engineering
ISBN : 9783319034225

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A Brief Introduction to Continuous Evolutionary Optimization by Oliver Kramer Pdf

Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel parameters of the Nadaraya-Watson estimator and a swarm-based iterative approach is presented for optimizing latent points in dimensionality reduction problems. Experiments on typical benchmark problems as well as numerous figures and diagrams illustrate the behavior of the introduced concepts and methods.

Evolutionary Algorithms in Management Applications

Jörg Biethahn,Volker Nissen
Evolutionary Algorithms in Management Applications Book PDF

Author : Jörg Biethahn,Volker Nissen
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 49,9 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642612176

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Evolutionary Algorithms in Management Applications by Jörg Biethahn,Volker Nissen Pdf

Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of adaptation, as formalised in his reproductive plans (later called Genetic Algorithms).

Introduction to Fuzzy Logic using MATLAB

S.N. Sivanandam,S. Sumathi,S. N. Deepa
Introduction to Fuzzy Logic using MATLAB Book PDF

Author : S.N. Sivanandam,S. Sumathi,S. N. Deepa
Publisher : Springer Science & Business Media
Page : 442 pages
File Size : 44,7 Mb
Release : 2006-10-28
Category : Technology & Engineering
ISBN : 9783540357810

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Introduction to Fuzzy Logic using MATLAB by S.N. Sivanandam,S. Sumathi,S. N. Deepa Pdf

This book provides a broad-ranging, but detailed overview of the basics of Fuzzy Logic. The fundamentals of Fuzzy Logic are discussed in detail, and illustrated with various solved examples. The book also deals with applications of Fuzzy Logic, to help readers more fully understand the concepts involved. Solutions to the problems are programmed using MATLAB 6.0, with simulated results. The MATLAB Fuzzy Logic toolbox is provided for easy reference.

Evolutionary Computation

Kenneth A. De Jong
Evolutionary Computation Book PDF

Author : Kenneth A. De Jong
Publisher : MIT Press
Page : 267 pages
File Size : 42,6 Mb
Release : 2006-02-03
Category : Computers
ISBN : 9780262041942

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Evolutionary Computation by Kenneth A. De Jong Pdf

This text is an introduction to the field of evolutionary computation. It approaches evolution strategies and genetic programming, as instances of a more general class of evolutionary algorithms.

Evolutionary Optimization Algorithms

Dan Simon
Evolutionary Optimization Algorithms Book PDF

Author : Dan Simon
Publisher : John Wiley & Sons
Page : 776 pages
File Size : 55,8 Mb
Release : 2013-06-13
Category : Mathematics
ISBN : 9781118659502

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Evolutionary Optimization Algorithms by Dan Simon Pdf

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

Applied Evolutionary Algorithms for Engineers using Python

Leonardo Azevedo Scardua
Applied Evolutionary Algorithms for Engineers using Python Book PDF

Author : Leonardo Azevedo Scardua
Publisher : CRC Press
Page : 225 pages
File Size : 42,6 Mb
Release : 2021-06-15
Category : Computers
ISBN : 9781000349801

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Applied Evolutionary Algorithms for Engineers using Python by Leonardo Azevedo Scardua Pdf

Applied Evolutionary Algorithms for Engineers with Python is written for students, scientists and engineers who need to apply evolutionary algorithms to practical optimization problems. The presentation of the theoretical background is complemented with didactical Python implementations of evolutionary algorithms that researchers have recently applied to complex optimization problems. Cases of successful application of evolutionary algorithms to real-world like optimization problems are presented, together with source code that allows the reader to gain insight into the idiosyncrasies of the practical application of evolutionary algorithms. Key Features Includes detailed descriptions of evolutionary algorithm paradigms Provides didactic implementations of the algorithms in Python, a programming language that has been widely adopted by the AI community Discusses the application of evolutionary algorithms to real-world optimization problems Presents successful cases of the application of evolutionary algorithms to complex optimization problems, with auxiliary source code.

Creative Evolutionary Systems

Peter Bentley,David W. Corne
Creative Evolutionary Systems Book PDF

Author : Peter Bentley,David W. Corne
Publisher : Morgan Kaufmann
Page : 618 pages
File Size : 51,7 Mb
Release : 2002
Category : Computers
ISBN : 9781558606739

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Creative Evolutionary Systems by Peter Bentley,David W. Corne Pdf

Written for computer scientists and students, and computer literate artists, designers and specialists in evolutionary computation, this text brings together the most advanced work in the use of evolutionary computation for creative results.

Evolutionary Algorithms

Alain Petrowski,Sana Ben-Hamida
Evolutionary Algorithms Book PDF

Author : Alain Petrowski,Sana Ben-Hamida
Publisher : John Wiley & Sons
Page : 256 pages
File Size : 47,8 Mb
Release : 2017-04-24
Category : Computers
ISBN : 9781848218048

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Evolutionary Algorithms by Alain Petrowski,Sana Ben-Hamida Pdf

Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.

Estimation of Distribution Algorithms

Pedro Larrañaga,José A. Lozano
Estimation of Distribution Algorithms Book PDF

Author : Pedro Larrañaga,José A. Lozano
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 50,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461515395

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Estimation of Distribution Algorithms by Pedro Larrañaga,José A. Lozano Pdf

Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is devoted to a new paradigm for evolutionary computation, named estimation of distribution algorithms (EDAs). This new class of algorithms generalizes genetic algorithms by replacing the crossover and mutation operators with learning and sampling from the probability distribution of the best individuals of the population at each iteration of the algorithm. Working in such a way, the relationships between the variables involved in the problem domain are explicitly and effectively captured and exploited. This text constitutes the first compilation and review of the techniques and applications of this new tool for performing evolutionary computation. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is clearly divided into three parts. Part I is dedicated to the foundations of EDAs. In this part, after introducing some probabilistic graphical models - Bayesian and Gaussian networks - a review of existing EDA approaches is presented, as well as some new methods based on more flexible probabilistic graphical models. A mathematical modeling of discrete EDAs is also presented. Part II covers several applications of EDAs in some classical optimization problems: the travelling salesman problem, the job scheduling problem, and the knapsack problem. EDAs are also applied to the optimization of some well-known combinatorial and continuous functions. Part III presents the application of EDAs to solve some problems that arise in the machine learning field: feature subset selection, feature weighting in K-NN classifiers, rule induction, partial abductive inference in Bayesian networks, partitional clustering, and the search for optimal weights in artificial neural networks. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is a useful and interesting tool for researchers working in the field of evolutionary computation and for engineers who face real-world optimization problems. This book may also be used by graduate students and researchers in computer science. `... I urge those who are interested in EDAs to study this well-crafted book today.' David E. Goldberg, University of Illinois Champaign-Urbana.

Evolutionary Optimization

Ruhul Sarker,Masoud Mohammadian,Xin Yao
Evolutionary Optimization Book PDF

Author : Ruhul Sarker,Masoud Mohammadian,Xin Yao
Publisher : Springer Science & Business Media
Page : 418 pages
File Size : 55,5 Mb
Release : 2006-04-11
Category : Business & Economics
ISBN : 9780306480416

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Evolutionary Optimization by Ruhul Sarker,Masoud Mohammadian,Xin Yao Pdf

Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.