Evolutionary Optimization Algorithms

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Evolutionary Optimization Algorithms

Dan Simon
Evolutionary Optimization Algorithms Book PDF

Author : Dan Simon
Publisher : John Wiley & Sons
Page : 776 pages
File Size : 55,5 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.

Evolutionary Optimization Algorithms

Altaf Q. H. Badar
Evolutionary Optimization Algorithms Book PDF

Author : Altaf Q. H. Badar
Publisher : CRC Press
Page : 273 pages
File Size : 51,5 Mb
Release : 2021-10-30
Category : Technology & Engineering
ISBN : 9781000462142

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Evolutionary Optimization Algorithms by Altaf Q. H. Badar Pdf

This comprehensive reference text discusses evolutionary optimization techniques, to find optimal solutions for single and multi-objective problems. The text presents each evolutionary optimization algorithm along with its history and other working equations. It also discusses variants and hybrids of optimization techniques. The text presents step-by-step solution to a problem and includes software’s like MATLAB and Python for solving optimization problems. It covers important optimization algorithms including single objective optimization, multi objective optimization, Heuristic optimization techniques, shuffled frog leaping algorithm, bacteria foraging algorithm and firefly algorithm. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, mechanical engineering, and computer science and engineering, this text: Provides step-by-step solution for each evolutionary optimization algorithm. Provides flowcharts and graphics for better understanding of optimization techniques. Discusses popular optimization techniques include particle swarm optimization and genetic algorithm. Presents every optimization technique along with the history and working equations. Includes latest software like Python and MATLAB.

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 : 41,7 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.

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 : 52,6 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 Computation and Optimization Algorithms in Software Engineering: Applications and Techniques

Chis, Monica
Evolutionary Computation and Optimization Algorithms in Software Engineering Applications and Techniques Book PDF

Author : Chis, Monica
Publisher : IGI Global
Page : 282 pages
File Size : 54,7 Mb
Release : 2010-06-30
Category : Education
ISBN : 9781615208104

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Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques by Chis, Monica Pdf

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques lays the foundation for the successful integration of evolutionary computation into software engineering. It surveys techniques ranging from genetic algorithms, to swarm optimization theory, to ant colony optimization, demonstrating their uses and capabilities. These techniques are applied to aspects of software engineering such as software testing, quality assessment, reliability assessment, and fault prediction models, among others, to providing researchers, scholars and students with the knowledge needed to expand this burgeoning application.

Hierarchical Bayesian Optimization Algorithm

Martin Pelikan
Hierarchical Bayesian Optimization Algorithm Book PDF

Author : Martin Pelikan
Publisher : Springer Science & Business Media
Page : 194 pages
File Size : 51,7 Mb
Release : 2005-02
Category : Computers
ISBN : 3540237747

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Hierarchical Bayesian Optimization Algorithm by Martin Pelikan Pdf

This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope. The algorithms are also extensively tested on two interesting classes of real-world problems: MAXSAT and Ising spin glasses with periodic boundary conditions in two and three dimensions. Experimental results validate the theoretical model and confirm that BOA and hBOA provide robust and scalable solution for nearly decomposable and hierarchical problems with only little problem-specific information.

Evolutionary Algorithms for Solving Multi-Objective Problems

Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Evolutionary Algorithms for Solving Multi Objective Problems Book PDF

Author : Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Publisher : Springer Science & Business Media
Page : 810 pages
File Size : 50,6 Mb
Release : 2007-08-26
Category : Computers
ISBN : 9780387367972

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Evolutionary Algorithms for Solving Multi-Objective Problems by Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen Pdf

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Evolutionary Optimization in Dynamic Environments

Jürgen Branke
Evolutionary Optimization in Dynamic Environments Book PDF

Author : Jürgen Branke
Publisher : Springer Science & Business Media
Page : 217 pages
File Size : 48,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461509110

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Evolutionary Optimization in Dynamic Environments by Jürgen Branke Pdf

Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to continuously and efficiently adapt a solution to a changing environment, find a good trade-off between solution quality and adaptation cost, find robust solutions whose quality is insensitive to changes in the environment, find flexible solutions which are not only good but that can be easily adapted when necessary. All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.

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 : 43,6 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.

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 : 48,7 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.

Evolutionary Algorithms and Neural Networks

Seyedali Mirjalili
Evolutionary Algorithms and Neural Networks Book PDF

Author : Seyedali Mirjalili
Publisher : Springer
Page : 156 pages
File Size : 40,8 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.

Soft Computing

Luigi Fortuna,Gianguido Rizzotto,Mario Lavorgna,Giuseppe Nunnari,Maria Gabriella Xibilia,Riccardo Caponetto
Soft Computing Book PDF

Author : Luigi Fortuna,Gianguido Rizzotto,Mario Lavorgna,Giuseppe Nunnari,Maria Gabriella Xibilia,Riccardo Caponetto
Publisher : Springer Science & Business Media
Page : 275 pages
File Size : 47,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447103578

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Soft Computing by Luigi Fortuna,Gianguido Rizzotto,Mario Lavorgna,Giuseppe Nunnari,Maria Gabriella Xibilia,Riccardo Caponetto Pdf

The book presents a clear understanding of a new type of computation system, the Cellular Neural Network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. The text describes how CNN will improve the soft-computation toolbox, and examines the many applications of soft computing to complex systems.

Evolutionary Algorithms

William M. Spears
Evolutionary Algorithms Book PDF

Author : William M. Spears
Publisher : Springer Science & Business Media
Page : 224 pages
File Size : 52,5 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9783662041994

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Evolutionary Algorithms by William M. Spears Pdf

Despite decades of work in evolutionary algorithms, there remains an uncertainty as to the relative benefits and detriments of using recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates important prior work and introduces new theoretical techniques for studying evolutionary algorithms. Consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. The focus allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.

Multi-Objective Optimization using Evolutionary Algorithms

Kalyanmoy Deb
Multi Objective Optimization using Evolutionary Algorithms Book PDF

Author : Kalyanmoy Deb
Publisher : John Wiley & Sons
Page : 540 pages
File Size : 43,5 Mb
Release : 2001-07-05
Category : Mathematics
ISBN : 047187339X

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Multi-Objective Optimization using Evolutionary Algorithms by Kalyanmoy Deb Pdf

Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.

Multimodal Optimization by Means of Evolutionary Algorithms

Mike Preuss
Multimodal Optimization by Means of Evolutionary Algorithms Book PDF

Author : Mike Preuss
Publisher : Springer
Page : 189 pages
File Size : 52,9 Mb
Release : 2015-11-27
Category : Computers
ISBN : 9783319074078

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Multimodal Optimization by Means of Evolutionary Algorithms by Mike Preuss Pdf

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.