Introduction to Evolutionary Computing

Introduction to Evolutionary Computing

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.

Author: A.E. Eiben

Publisher: Springer Science & Business Media

ISBN: 3540401849

Category: Computers

Page: 300

View: 624

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.
Categories: Computers

Representations for Genetic and Evolutionary Algorithms

Representations for Genetic and Evolutionary Algorithms

This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance.

Author: Franz Rothlauf

Publisher: Springer Science & Business Media

ISBN: 3540324445

Category: Technology & Engineering

Page: 325

View: 397

In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.
Categories: Technology & Engineering

Introduction to Evolutionary Algorithms

Introduction to Evolutionary Algorithms

Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms.

Author: Xinjie Yu

Publisher: Springer Science & Business Media

ISBN: 1849961298

Category: Computers

Page: 422

View: 464

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.
Categories: Computers

Evolutionary Computation

Evolutionary Computation

Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving.

Author: D. Dumitrescu

Publisher: CRC Press

ISBN: 0849305888

Category: Computers

Page: 424

View: 675

Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.
Categories: Computers

Evolutionary Computation 1

Evolutionary Computation 1

This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming.

Author: Thomas Baeck

Publisher: CRC Press

ISBN: 0750306645

Category: Mathematics

Page: 378

View: 880

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.
Categories: Mathematics

Parameter Setting in Evolutionary Algorithms

Parameter Setting in Evolutionary Algorithms

Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves.

Author: F.J. Lobo

Publisher: Springer Science & Business Media

ISBN: 9783540694311

Category: Mathematics

Page: 318

View: 814

One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
Categories: Mathematics

Genetic Algorithms Data Structures Evolution Programs

Genetic Algorithms   Data Structures   Evolution Programs

This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.

Author: Zbigniew Michalewicz

Publisher: Springer Science & Business Media

ISBN: 9783662033159

Category: Computers

Page: 387

View: 193

Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.
Categories: Computers

GECCO 2005

GECCO 2005

Author:

Publisher:

ISBN: 1595930108

Category: Genetic algorithms

Page:

View: 165

Categories: Genetic algorithms

An Introduction to Genetic Algorithms

An Introduction to Genetic Algorithms

Genetic algorithms : an overview - Genetic algorithms in problem solving - Genetic algorithms in scientific models - Theoretical foundations of genetic algorithms - Implementing a genetic algorithm.

Author: Melanie Mitchell

Publisher: MIT Press

ISBN: 0262631857

Category: Computers

Page: 209

View: 923

Genetic algorithms : an overview - Genetic algorithms in problem solving - Genetic algorithms in scientific models - Theoretical foundations of genetic algorithms - Implementing a genetic algorithm.
Categories: Computers

Evolutionary Computation for Modeling and Optimization

Evolutionary Computation for Modeling and Optimization

This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods.

Author: Daniel Ashlock

Publisher: Springer Science & Business Media

ISBN: 0387319093

Category: Computers

Page: 572

View: 985

Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.
Categories: Computers

Introduction to Genetic Algorithms

Introduction to Genetic Algorithms

This book offers a basic introduction to genetic algorithms.

Author: S.N. Sivanandam

Publisher: Springer Science & Business Media

ISBN: 9783540731900

Category: Mathematics

Page: 442

View: 782

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.
Categories: Mathematics

Natural Computing with Python

Natural Computing with Python

This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing.

Author: Giancarlo Zaccone

Publisher: BPB Publications

ISBN: 9789388511612

Category: Computers

Page: 278

View: 851

Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms. DESCRIPTION Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, you’ll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePy and Cellular Automata techniques such as Game of Life, Langton's ant, etc. The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. KEY FEATURES Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals WHAT WILL YOU LEARN Mastering Artificial Neural Networks Developing Artificial Intelligence systems Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computation WHO THIS BOOK IS FOR This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book. Table of Contents Neural Networks Deep Learning Genetic Programming Swarm Intelligence Cellular Automata Fractals Quantum Computing DNA Computing
Categories: Computers

Evolutionary Algorithms

Evolutionary Algorithms

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.

Author: Alain Petrowski

Publisher: John Wiley & Sons

ISBN: 9781848218048

Category: Computers

Page: 256

View: 571

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.
Categories: Computers

Evolutionary Algorithms in Engineering and Computer Science

Evolutionary Algorithms in Engineering and Computer Science

Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing.

Author: K. Miettinen

Publisher: John Wiley & Sons

ISBN: STANFORD:36105023625531

Category: Computers

Page: 483

View: 580

Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyväskylä, Finland M. M. Mäkelä, University of Jyväskylä, Finland P. Neittaanmäki, University of Jyväskylä, Finland J. Périaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics. This rapidly growing field, with its deep understanding and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest and value to all postgraduates, research scientists and practitioners facing complex optimization problems.
Categories: Computers

Evolutionary Algorithms in Theory and Practice

Evolutionary Algorithms in Theory and Practice

A comparison of evolutionary algorithms.

Author: Thomas Bäck

Publisher: Oxford University Press on Demand

ISBN: 9780195099713

Category: Social Science

Page: 314

View: 322

A comparison of evolutionary algorithms. Organic evolution and problem solving. Biological background. Evolutionary algorithms and artificial intelligence. Evolutionary algorithms and global optimization. Early approaches. Specific evolutionary algorithms. Evolution strategies. Evolutionary programming. Genetic algorithms. Artificial landscapes. An empirical comparison. Extending genetic algorithms. Selection. Selection mechanisms. Experimental investigation of selection. Mutation. Simplified genetic algorithms. An experiment in meta-evolution. Summary and outlook. Data for the fletcher-powell function. Data from selection experiments. Software. The multiprocessor environment; mathematical symbols.
Categories: Social Science

Handbook of Evolutionary Computation

Handbook of Evolutionary Computation

This work is intended to become the standard reference resource for the evolutionary computation community.

Author: Thomas Bäck

Publisher: Inst of Physics Pub Incorporated

ISBN: 0750303921

Category: Computers

Page: 988

View: 881

Many scientists and engineers now use the paradigms of evolutionary computation (genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids thereof) to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. Recently there have been vigorous initiatives to promote cross-fertilization between the EC paradigms, and also to combine these paradigms with other approaches such as neural networks to create hybrid systems with enhanced capabilities. To address the need for speedy dissemination of new ideas in these fields, and also to assist in cross-disciplinary communications and understanding, Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications. This work is intended to become the standard reference resource for the evolutionary computation community. The Handbook of Evolutionary Computation will be available in loose-leaf print form, as well as in an electronic version that combines both CD-ROM and on-line (World Wide Web) access to its contents. Regularly published supplements will be available on a subscription basis.
Categories: Computers

A Field Guide to Genetic Programming

A Field Guide to Genetic Programming

This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.

Author:

Publisher: Lulu.com

ISBN: 9781409200734

Category: Computers

Page: 233

View: 698

Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.
Categories: Computers

Genetic and Evolutionary Computing

Genetic and Evolutionary Computing

Proceedings of the Seventh International Conference on Genetic and
Evolutionary Computing, ICGEC 2013, August 25 - 27, 2013 - Prague, Czech
Republic Jeng-Shyang Pan, Pavel Krömer, Václav Snášel ...

Author: Jeng-Shyang Pan

Publisher: Springer Science & Business Media

ISBN: 9783319017969

Category: Computers

Page: 410

View: 636

Genetic and Evolutionary Computing This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2013, the 7th International Conference on Genetic and Evolutionary Computing. The conference this year was technically co-sponsored by The Waseda University in Japan, Kaohsiung University of Applied Science in Taiwan, and VSB-Technical University of Ostrava. ICGEC 2013 was held in Prague, Czech Republic. Prague is one of the most beautiful cities in the world whose magical atmosphere has been shaped over ten centuries. Places of the greatest tourist interest are on the Royal Route running from the Powder Tower through Celetna Street to Old Town Square, then across Charles Bridge through the Lesser Town up to the Hradcany Castle. One should not miss the Jewish Town, and the National Gallery with its fine collection of Czech Gothic art, collection of old European art, and a beautiful collection of French art. The conference was intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. The main topics of ICGEC 2013 included Intelligent Computing, Evolutionary Computing, Genetic Computing, and Grid Computing.
Categories: Computers

Genetic and Evolutionary Computing

Genetic and Evolutionary Computing

Proceeding of the Eighth International Conference on Genetic and Evolutionary
Computing, October 18-20, 2014, Nanchang, China Hui Sun, Chin-Yu Yang,
Chun-Wei Lin, Jeng-Shyang Pan, Vaclav Snasel, Ajith Abraham.

Author: Hui Sun

Publisher: Springer

ISBN: 9783319122861

Category: Computers

Page: 428

View: 381

This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2014, the 8th International Conference on Genetic and Evolutionary Computing. The conference this year was technically co-sponsored by Nanchang Institute of Technology in China, Kaohsiung University of Applied Science in Taiwan, and VSB-Technical University of Ostrava. ICGEC 2014 is held from 18-20 October 2014 in Nanchang, China. Nanchang is one of is the capital of Jiangxi Province in southeastern China, located in the north-central portion of the province. As it is bounded on the west by the Jiuling Mountains, and on the east by Poyang Lake, it is famous for its scenery, rich history and cultural sites. Because of its central location relative to the Yangtze and Pearl River Delta regions, it is a major railroad hub in Southern China. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing.
Categories: Computers