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Author : Daniel Ashlock
Publisher : Springer Science & Business Media
Page : 578 pages
File Size : 45,9 Mb
Release : 2006-04-04
Category : Computers
ISBN : 9780387319094
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.
Author : Samuelson Hong, Wei-Chiang
Publisher : IGI Global
Page : 357 pages
File Size : 52,8 Mb
Release : 2013-03-31
Category : Computers
ISBN : 9781466636293
Evolutionary computation has emerged as a major topic in the scientific community as many of its techniques have successfully been applied to solve problems in a wide variety of fields. Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation provides comprehensive research on emerging theories and its aspects on intelligent computation. Particularly focusing on breaking trends in evolutionary computing, algorithms, and programming, this publication serves to support professionals, government employees, policy and decision makers, as well as students in this scientific field.
Author : Silja Meyer-Nieberg,Nadiia Leopold,Tobias Uhlig
Publisher : Springer
Page : 60 pages
File Size : 48,6 Mb
Release : 2019-07-26
Category : Business & Economics
ISBN : 9783030262150
This SpringerBrief bridges the gap between the areas of simulation studies on the one hand, and optimization with natural computing on the other. Since natural computing methods have been applied with great success in several application areas, a review concerning potential benefits and pitfalls for simulation studies is merited. The brief presents such an overview and combines it with an introduction to natural computing and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review which covers both the methodological background and recent application cases. The brief is intended to serve two purposes: First, it can be used to gain more information concerning natural computing, its major dialects, and their usage for simulation studies. It also covers the areas of multi-objective optimization and neuroevolution. While the latter is only seldom mentioned in connection with simulation studies, it is a powerful potential technique. Second, the reader is provided with an overview of several areas of simulation-based optimization which range from logistic problems to engineering tasks. Additionally, the brief focuses on the usage of surrogate and meta-models. The brief presents recent application examples.
Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 54,5 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941
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.
Author : Kay Chen Tan,Eik Fun Khor,Tong Heng Lee
Publisher : Springer Science & Business Media
Page : 295 pages
File Size : 41,6 Mb
Release : 2005-11-28
Category : Computers
ISBN : 9781846281327
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 : Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński
Publisher : Springer
Page : 470 pages
File Size : 48,7 Mb
Release : 2008-10-18
Category : Computers
ISBN : 9783540889083
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 : Anil Menon
Publisher : Springer Science & Business Media
Page : 271 pages
File Size : 49,5 Mb
Release : 2006-04-11
Category : Computers
ISBN : 9781402077821
Frontiers of Evolutionary Computation brings together eleven contributions by international leading researchers discussing what significant issues still remain unresolved in the field of Evolutionary Computation (Ee. They explore such topics as the role of building blocks, the balancing of exploration with exploitation, the modeling of EC algorithms, the connection with optimization theory and the role of EC as a meta-heuristic method, to name a few. The articles feature a mixture of informal discussion interspersed with formal statements, thus providing the reader an opportunity to observe a wide range of EC problems from the investigative perspective of world-renowned researchers. These prominent researchers include: Heinz M]hlenbein, Kenneth De Jong, Carlos Cotta and Pablo Moscato, Lee Altenberg, Gary A. Kochenberger, Fred Glover, Bahram Alidaee and Cesar Rego, William G. Macready, Christopher R. Stephens and Riccardo Poli, Lothar M. Schmitt, John R. Koza, Matthew J. Street and Martin A. Keane, Vivek Balaraman, Wolfgang Banzhaf and Julian Miller.
Author : Ashish M. Gujarathi,B. V. Babu
Publisher : CRC Press
Page : 652 pages
File Size : 55,7 Mb
Release : 2016-12-01
Category : Computers
ISBN : 9781315342160
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 : Ernesto Sanchez,Giovanni Squillero,Alberto Tonda
Publisher : Springer Science & Business Media
Page : 137 pages
File Size : 48,6 Mb
Release : 2012-01-28
Category : Technology & Engineering
ISBN : 9783642274671
"Industrial applications of evolutionary algorithms" is intended as a resource for both experienced users of evolutionary algorithms and researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, advice on solving issues related to fitness computation or modeling, and suggestions on how to set the appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of several classes of evolutionary algorithms exploited to solve different problems. Inside, scholars will find useful examples on how to fill the gap between purely theoretical examples and industrial problems. The collection of case studies presented is also extremely appealing for anyone interested in Evolutionary Computation, but without direct access to extensive technical literature on the subject. After the introduction, each chapter in the book presents a test case, and is organized so that it can be read independently from the rest: all the information needed to understand the problem and the approach is reported in each part. Chapters are grouped by three themes of particular interest for real-world applications, namely prototype-based validation, reliability and test generation. The authors hope that this volume will help to expose the flexibility and efficiency of evolutionary techniques, encouraging more companies to adopt them; and that, most of all, you will enjoy your reading.
Author : Ajith Abraham,Robert Goldberg
Publisher : Springer Science & Business Media
Page : 313 pages
File Size : 49,5 Mb
Release : 2005-09-05
Category : Computers
ISBN : 9781846281372
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 : Dan Simon
Publisher : John Wiley & Sons
Page : 776 pages
File Size : 52,7 Mb
Release : 2013-06-13
Category : Mathematics
ISBN : 9781118659502
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.
Author : Benjamin Doerr,Frank Neumann
Publisher : Springer Nature
Page : 506 pages
File Size : 43,5 Mb
Release : 2019-11-20
Category : Computers
ISBN : 9783030294144
This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming. Throughout the book the contributing authors try to develop an understanding for how these methods work, and why they are so successful in many applications. The book will be useful for students and researchers in theoretical computer science and evolutionary computing.
Author : Haiping Ma,Dan Simon
Publisher : John Wiley & Sons
Page : 356 pages
File Size : 55,8 Mb
Release : 2017-02-06
Category : Computers
ISBN : 9781848218079
Evolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science of biogeography, which researches the migration patterns of species. These migration paradigms provide the main logic behind BBO. Due to the cross-disciplinary nature of the optimization problems, there is a need to develop multiple approaches to tackle them and to study the theoretical reasoning behind their performance. This book explains the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.
Author : Dirk V. Arnold
Publisher : Springer Science & Business Media
Page : 176 pages
File Size : 52,8 Mb
Release : 2002
Category : Computers
ISBN : 1402071051
Noise is a common factor in most real-world optimization problems. Sources of noise can include physical measurement limitations, stochastic simulation models, incomplete sampling of large spaces and human-computer interaction. Evolutionary algorithms are general, nature-inspired heuristics for numerical search and optimization that are frequently observed to be particularly robust with regard to the effects of noise.
Author : Daniel Ashlock
Publisher : Springer Science & Business Media
Page : 600 pages
File Size : 41,9 Mb
Release : 2005-12-15
Category : Computers
ISBN : 0387221964
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.
