Multiobjective Evolutionary Algorithms And Applications

Author : Ajith Abraham,Robert Goldberg
Publisher : Springer Science & Business Media
Page : 313 pages
File Size : 44,9 Mb
Release : 2005-09-05
Category : Computers
ISBN : 9781846281372

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Evolutionary Multiobjective Optimization by Ajith Abraham,Robert Goldberg Pdf

Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.

Author : Carlos A. Coello Coello,Gary B. Lamont
Publisher : World Scientific
Page : 792 pages
File Size : 41,9 Mb
Release : 2004
Category : Computers
ISBN : 9789812561060

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Applications of Multi-objective Evolutionary Algorithms by Carlos A. Coello Coello,Gary B. Lamont Pdf

- Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique monograph covering a wide spectrum of real-world applications - Step-by-step discussion of MOEA applications in a variety of domains

Author : Kay Chen Tan,Eik Fun Khor,Tong Heng Lee
Publisher : Springer Science & Business Media
Page : 314 pages
File Size : 41,6 Mb
Release : 2005-05-04
Category : Computers
ISBN : 1852338369

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Multiobjective Evolutionary Algorithms and Applications by Kay Chen Tan,Eik Fun Khor,Tong Heng Lee Pdf

Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. Covers the authors’ recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.

Author : Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Publisher : Springer Science & Business Media
Page : 810 pages
File Size : 51,9 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.

Author : Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Publisher : Springer Science & Business Media
Page : 810 pages
File Size : 47,5 Mb
Release : 2007-09-18
Category : Computers
ISBN : 9780387332543

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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.

Author : Kalyanmoy Deb
Publisher : John Wiley & Sons
Page : 540 pages
File Size : 55,6 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.

Author : Carlos Coello Coello,David A. Van Veldhuizen,Gary B. Lamont
Publisher : Springer Science & Business Media
Page : 600 pages
File Size : 41,6 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9781475751840

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

Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.

Author : Joshua Knowles,David Corne,Kalyanmoy Deb
Publisher : Springer Science & Business Media
Page : 413 pages
File Size : 51,7 Mb
Release : 2008-01-28
Category : Computers
ISBN : 9783540729631

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Multiobjective Problem Solving from Nature by Joshua Knowles,David Corne,Kalyanmoy Deb Pdf

This text examines how multiobjective evolutionary algorithms and related techniques can be used to solve problems, particularly in the disciplines of science and engineering. Contributions by leading researchers show how the concept of multiobjective optimization can be used to reformulate and resolve problems in areas such as constrained optimization, co-evolution, classification, inverse modeling, and design.

Author : Slim Bechikh,Rituparna Datta,Abhishek Gupta
Publisher : Springer
Page : 179 pages
File Size : 44,7 Mb
Release : 2016-08-09
Category : Technology & Engineering
ISBN : 9783319429786

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Recent Advances in Evolutionary Multi-objective Optimization by Slim Bechikh,Rituparna Datta,Abhishek Gupta Pdf

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

Author : Nadia Nedjah,Luiza De Macedo Mourelle,Heitor Silverio Lopes
Publisher : CRC Press
Page : 218 pages
File Size : 50,7 Mb
Release : 2020-07-15
Category : Computers
ISBN : 9781498780292

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Evolutionary Multi-Objective System Design by Nadia Nedjah,Luiza De Macedo Mourelle,Heitor Silverio Lopes Pdf

Real-world engineering problems often require concurrent optimization of several design objectives, which are conflicting in cases. This type of optimization is generally called multi-objective or multi-criterion optimization. The area of research that applies evolutionary methodologies to multi-objective optimization is of special and growing interest. It brings a viable computational solution to many real-world problems. Generally, multi-objective engineering problems do not have a straightforward optimal design. These kinds of problems usually inspire several solutions of equal efficiency, which achieve different trade-offs. Decision makers’ preferences are normally used to select the most adequate design. Such preferences may be dictated before or after the optimization takes place. They may also be introduced interactively at different levels of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods usually aim at a single solution while the evolutionary methods provide a whole set of so-called Pareto-optimal solutions. Evolutionary Multi-Objective System Design: Theory and Applications provides a representation of the state-of-the-art in evolutionary multi-objective optimization research area and related new trends. It reports many innovative designs yielded by the application of such optimization methods. It also presents the application of multi-objective optimization to the following problems: Embrittlement of stainless steel coated electrodes Learning fuzzy rules from imbalanced datasets Combining multi-objective evolutionary algorithms with collective intelligence Fuzzy gain scheduling control Smart placement of roadside units in vehicular networks Combining multi-objective evolutionary algorithms with quasi-simplex local search Design of robust substitution boxes Protein structure prediction problem Core assignment for efficient network-on-chip-based system design

Author : Eckart Zitzler
Publisher : Unknown
Page : 122 pages
File Size : 55,7 Mb
Release : 1999
Category : Computer algorithms
ISBN : 3826568311

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Evolutionary Algorithms for Multiobjective Optimization by Eckart Zitzler Pdf

Author : Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński
Publisher : Springer
Page : 470 pages
File Size : 41,6 Mb
Release : 2008-10-18
Category : Computers
ISBN : 9783540889083

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Multiobjective Optimization by Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński Pdf

Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

Author : Ashish M. Gujarathi,B. V. Babu
Publisher : CRC Press
Page : 652 pages
File Size : 45,8 Mb
Release : 2016-12-01
Category : Computers
ISBN : 9781315342160

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Evolutionary Computation by Ashish M. Gujarathi,B. V. Babu Pdf

Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization

Author : Eckart Zitzler,Kalyanmoy Deb,Lothar Thiele,Carlos Coello Coello,David Corne
Publisher : Springer
Page : 714 pages
File Size : 55,6 Mb
Release : 2003-06-29
Category : Mathematics
ISBN : 9783540447191

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Evolutionary Multi-Criterion Optimization by Eckart Zitzler,Kalyanmoy Deb,Lothar Thiele,Carlos Coello Coello,David Corne Pdf

This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001. The 45 revised full papers presented were carefully reviewed and selected from a total of 87 submissions. Also included are two tutorial surveys and two invited papers. The book is organized in topical sections on algorithm improvements, performance assessment and comparison, constraint handling and problem decomposition, uncertainty and noise, hybrid and alternative methods, scheduling, and applications of multi-objective optimization in a variety of fields.

Author : Xinjie Yu,Mitsuo Gen
Publisher : Springer Science & Business Media
Page : 422 pages
File Size : 49,9 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.