Evolutionary Algorithms In Engineering And Computer Science PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Evolutionary Algorithms In Engineering And Computer Science PDF full book. Access full book title Evolutionary Algorithms In Engineering And Computer Science.

Evolutionary Algorithms

Evolutionary Algorithms
Author: Alain Petrowski
Publisher: John Wiley & Sons
Total Pages: 256
Release: 2017-04-24
Genre: Computers
ISBN: 1848218044
GET BOOK

Download Evolutionary Algorithms Book in PDF, ePub and Kindle

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.

Evolutionary Algorithms in Engineering Applications

Evolutionary Algorithms in Engineering Applications
Author: Dipankar Dasgupta
Publisher: Springer Science & Business Media
Total Pages: 561
Release: 2013-06-29
Genre: Computers
ISBN: 3662034239
GET BOOK

Download Evolutionary Algorithms in Engineering Applications Book in PDF, ePub and Kindle

Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques
Author: Chis, Monica
Publisher: IGI Global
Total Pages: 282
Release: 2010-06-30
Genre: Education
ISBN: 1615208100
GET BOOK

Download Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques Book in PDF, ePub and Kindle

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.

Introduction to Evolutionary Algorithms

Introduction to Evolutionary Algorithms
Author: Xinjie Yu
Publisher: Springer Science & Business Media
Total Pages: 427
Release: 2010-06-10
Genre: Computers
ISBN: 1849961298
GET BOOK

Download Introduction to Evolutionary Algorithms Book in PDF, ePub and Kindle

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.

Genetic Algorithms in Engineering and Computer Science

Genetic Algorithms in Engineering and Computer Science
Author: G. Winter
Publisher:
Total Pages: 486
Release: 1995
Genre: Computers
ISBN:
GET BOOK

Download Genetic Algorithms in Engineering and Computer Science Book in PDF, ePub and Kindle

Genetic Algorithms in Engineering and Computer Science Edited by G. Winter University of Las Palmas, Canary Islands, Spain J. Périaux Dassault Aviation, Saint Cloud, France M. Galán P. Cuesta University of Las Palmas, Canary Islands, Spain This attractive book alerts us to the existence of evolution based software — Genetic Algorithms and Evolution Strategies—used for the study of complex systems and difficult optimization problems unresolved until now. Evolution algorithms are artificial intelligence techniques which mimic nature according to the "survival of the fittest" (Darwin’s principle). They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore large search spaces and find near-global optima than traditional optimization methods. The objectives of this volume are two-fold: to present a compendium of state-of-the-art lectures delivered by recognized experts in the field on theoretical, numerical and applied aspects of Genetic Algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems. to provide a bridge between Artificial Intelligence and Scientific Computing in order to increase the performance of evolution programs for solving real life problems. Fluid dynamics, structure mechanics, electromagnetics, automation control, resource optimization, image processing and economics are the featured multi-disciplinary areas among others in Engineering and Applied Sciences where evolution works impressively well. This volume is aimed at graduate students, applied mathematicians, computer scientists, researchers and engineers who face challenging design optimization problems in Industry. They will enjoy implementing new programs using these evolution techniques which have been experimented with by Nature for 3.5 billion years.

Evolutionary Computation for Modeling and Optimization

Evolutionary Computation for Modeling and Optimization
Author: Daniel Ashlock
Publisher: Springer Science & Business Media
Total Pages: 578
Release: 2006-04-04
Genre: Computers
ISBN: 0387319093
GET BOOK

Download Evolutionary Computation for Modeling and Optimization Book in PDF, ePub and Kindle

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

Evolutionary Algorithms in Engineering and Computer Science

Evolutionary Algorithms in Engineering and Computer Science
Author: K. Miettinen
Publisher: John Wiley & Sons
Total Pages: 512
Release: 1999-07-09
Genre: Computers
ISBN:
GET BOOK

Download Evolutionary Algorithms in Engineering and Computer Science Book in PDF, ePub and Kindle

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.

Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems
Author: Carlos Coello Coello
Publisher: Springer Science & Business Media
Total Pages: 810
Release: 2007-08-26
Genre: Computers
ISBN: 0387367977
GET BOOK

Download Evolutionary Algorithms for Solving Multi-Objective Problems Book in PDF, ePub and Kindle

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.

Genetic Algorithms and Engineering Optimization

Genetic Algorithms and Engineering Optimization
Author: Mitsuo Gen
Publisher: John Wiley & Sons
Total Pages: 520
Release: 1999-12-28
Genre: Technology & Engineering
ISBN: 9780471315315
GET BOOK

Download Genetic Algorithms and Engineering Optimization Book in PDF, ePub and Kindle

Im Mittelpunkt dieses Buches steht eines der wichtigsten Optimierungsverfahren der industriellen Ingenieurtechnik: Mit Hilfe genetischer Algorithmen lassen sich Qualität, Design und Zuverlässigkeit von Produkten entscheidend verbessern. Das Verfahren beruht auf der Wahrscheinlichkeitstheorie und lehnt sich an die Prinzipien der biologischen Vererbung an: Die Eigenschaften des Produkts werden, unter Beachtung der äußeren Randbedingungen, schrittweise optimiert. Ein hochaktueller Band international anerkannter Autoren. (03/00)

Analyzing Evolutionary Algorithms

Analyzing Evolutionary Algorithms
Author: Thomas Jansen
Publisher: Springer Science & Business Media
Total Pages: 264
Release: 2013-01-24
Genre: Computers
ISBN: 364217339X
GET BOOK

Download Analyzing Evolutionary Algorithms Book in PDF, ePub and Kindle

Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. In this book the author provides an introduction to the methods used to analyze evolutionary algorithms and other randomized search heuristics. He starts with an algorithmic and modular perspective and gives guidelines for the design of evolutionary algorithms. He then places the approach in the broader research context with a chapter on theoretical perspectives. By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step. This main part is followed by a chapter covering practical applications of these methods. The notational and mathematical basics are covered in an appendix, the results presented are derived in detail, and each chapter ends with detailed comments and pointers to further reading. So the book is a useful reference for both graduate students and researchers engaged with the theoretical analysis of such algorithms.