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Applications Of Multi Objective Evolutionary Algorithms


Applications Of Multi Objective Evolutionary Algorithms
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Applications Of Multi Objective Evolutionary Algorithms


Applications Of Multi Objective Evolutionary Algorithms
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Author : Carlos A. Coello Coello
language : en
Publisher: World Scientific
Release Date : 2004

Applications Of Multi Objective Evolutionary Algorithms written by Carlos A. Coello Coello and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.


- 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



Evolutionary Algorithms For Solving Multi Objective Problems


Evolutionary Algorithms For Solving Multi Objective Problems
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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-26

Evolutionary Algorithms For Solving Multi Objective Problems written by Carlos Coello Coello and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-26 with Computers categories.


Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. 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, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.



Evolutionary Multiobjective Optimization


Evolutionary Multiobjective Optimization
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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-04-22

Evolutionary Multiobjective Optimization written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-22 with Computers categories.


Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts. Important features include: Detailed overview of all the multiobjective optimization paradigms using evolutionary algorithms Excellent coverage of timely, advanced multiobjective optimization topics State-of-the-art theoretical research and application developments Chapters authored by pioneers in the field Academics and industrial scientists as well as engineers engaged in research, development and application of evolutionary algorithm based Multiobjective Optimization will find the comprehensive coverage of this book invaluable.



Recent Advances In Evolutionary Multi Objective Optimization


Recent Advances In Evolutionary Multi Objective Optimization
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Author : Slim Bechikh
language : en
Publisher: Springer
Release Date : 2016-08-09

Recent Advances In Evolutionary Multi Objective Optimization written by Slim Bechikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-09 with Technology & Engineering categories.


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.



Applications Of Multi Objective Evolutionary Algorithms


Applications Of Multi Objective Evolutionary Algorithms
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Author : Carlos A Coello Coello
language : en
Publisher: World Scientific
Release Date : 2004-12-08

Applications Of Multi Objective Evolutionary Algorithms written by Carlos A Coello Coello and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-08 with Computers categories.


This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.



Multi Objective Optimization Using Evolutionary Algorithms


Multi Objective Optimization Using Evolutionary Algorithms
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Author : Kalyanmoy Deb
language : en
Publisher: John Wiley & Sons
Release Date : 2001-07-05

Multi Objective Optimization Using Evolutionary Algorithms written by Kalyanmoy Deb and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-05 with Mathematics categories.


Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.



Advances In Evolutionary Computing


Advances In Evolutionary Computing
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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advances In Evolutionary Computing written by Ashish Ghosh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution; thus the aim of designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution. These algo rithms are classified into three main categories, depending more on historical development than on major functional techniques. In fact, their biological basis is essentially the same. Hence EC = GA uGP u ES uEP EC = Evolutionary Computing GA = Genetic Algorithms,GP = Genetic Programming ES = Evolution Strategies,EP = Evolutionary Programming Although the details of biological evolution are not completely understood (even nowadays), there is some strong experimental evidence to support the following points: • Evolution is a process operating on chromosomes rather than on organ isms. • Natural selection is the mechanism that selects organisms which are well adapted to the environment toreproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage that includes mutation (which causes the chromosomes of offspring to be dif ferent from those of the parents) and recombination (which combines the chromosomes of the parents to produce the offspring). Based upon these features, the previously mentioned three models of evolutionary computing were independently (and almost simultaneously) de veloped. An evolutionary algorithm (EA) is an iterative and stochastic process that operates on a set of individuals (called a population).



Evolutionary Multi Criterion Optimization


Evolutionary Multi Criterion Optimization
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Author : Eckart Zitzler
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-02-28

Evolutionary Multi Criterion Optimization written by Eckart Zitzler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-02-28 with Business & Economics categories.


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.



Evolutionary Optimization


Evolutionary Optimization
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Author : Ruhul Sarker
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-11

Evolutionary Optimization written by Ruhul Sarker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-11 with Business & Economics categories.


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.



Multi Objective Optimization


Multi Objective Optimization
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Author : Gade Pandu Rangaiah
language : en
Publisher: World Scientific
Release Date : 2009

Multi Objective Optimization written by Gade Pandu Rangaiah and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Technology & Engineering categories.


Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed interest, this monograph presents the recent and ongoing research in multi-optimization techniques and their applications in chemical engineering. Following a brief introduction and general review on the development of multi-objective optimization applications in chemical engineering since 2000, the book gives a description of selected multi-objective techniques and then goes on to discuss chemical engineering applications. These applications are from diverse areas within chemical engineering, and are presented in detail. All chapters will be of interest to researchers in multi-objective optimization and/or chemical engineering; they can be read individually and used in one''s learning and research. Several exercises are included at the end of many chapters, for use by both practicing engineers and students.