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Author : Cem Safak Sahin
Publisher :
ISBN 13 :
Total Pages : 342 pages
Book Rating : 4.:/5 (733 download)
Download or read book Design and Performance Analysis of Genetic Algorithms for Topology Control Problems written by Cem Safak Sahin and published by . This book was released on 2010 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Xinggang Liu
Publisher :
ISBN 13 :
Total Pages : 252 pages
Book Rating : 4.:/5 (352 download)
Download or read book Performance Analysis of the Genetic Algorithm and Its Applications written by Xinggang Liu and published by . This book was released on 1995 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ali Selamat
Publisher : Springer
ISBN 13 : 3642365469
Total Pages : 542 pages
Book Rating : 4.6/5 (423 download)
Download or read book Intelligent Information and Database Systems written by Ali Selamat and published by Springer. This book was released on 2013-02-26 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 7802 and LNAI 7803 constitutes the refereed proceedings of the 5th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2013, held in Kuala Lumpur, Malaysia in March 2013. The 108 revised papers presented were carefully reviewed and selected from numerous submissions. The papers included are grouped into topical sections on: innovations in intelligent computation and applications; intelligent database systems; intelligent information systems; tools and applications; intelligent recommender systems; multiple modal approach to machine learning; engineering knowledge and semantic systems; computational biology and bioinformatics; computational intelligence; modeling and optimization techniques in information systems, database systems and industrial systems; intelligent supply chains; applied data mining for semantic Web; semantic Web and ontology; integration of information systems; and conceptual modeling in advanced database systems.
Author : Hermrean Wong
Publisher :
ISBN 13 :
Total Pages : 74 pages
Book Rating : 4.:/5 (115 download)
Download or read book Performance Analysis for Genetic Algorithms written by Hermrean Wong and published by . This book was released on 1995 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms have been shown effective for solving complex optimization problems such as job scheduling, machine learning, pattern recognition, and assembly planning. Due to the random process involved in genetic algorithms, the analysis of performance characteristics of genetic algorithms is a challenging research topic. Studied in this dissertation are methods to analyze convergence of genetic algorithms and to investigate whether modifications made to genetic algorithms, such as varying the operator rates during the iterative process, improve their performance. Both statistical analysis, which is used for investigation of different modifications to the genetic algorithm, and probability analysis, which is used to derive the expectation of convergence, are used in the study. The Wilcoxon signed rank test is used to examine the effects of changing parameters in genetic algorithms during the iterations. A Markov chain is derived to show how the random selection process affects the genetic evolution, including the so called genetic drift and preferential selection. A link distance is introduced as a numerical index for the study of the convergence process of order-based genetic algorithms. Also studied are the effects of random selection, mutation operator, and the combination of both to the expected average link distance. The genetic drift is shown to enforce the convergence exponentially with increase in the number of iterations. The mutation operator, on the other hand, suppresses the convergence. The combined results of these two parameters lead to a general formula for the estimation of the expected number of iterations needed to achieve convergence for the order-based genetic algorithm with selection and mutation and provide important insights about how order-based genetic algorithms converge.
Author : IEEE Staff
Publisher :
ISBN 13 : 9781479984343
Total Pages : pages
Book Rating : 4.9/5 (843 download)
Download or read book 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE) written by IEEE Staff and published by . This book was released on 2015-02-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference on Futuristic Trends in Computational analysis and Knowledge management is aimed to create a unique platform for academicians and the corporate big wigs to brainstorm and create a road map for futuristic trends in computational analysis and knowledge management
Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799880990
Total Pages : 1534 pages
Book Rating : 4.7/5 (998 download)
Download or read book Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-12-05 with total page 1534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
Author : Dimitri Knjazew
Publisher : Springer Science & Business Media
ISBN 13 : 9780792374602
Total Pages : 180 pages
Book Rating : 4.3/5 (746 download)
Download or read book OmeGA written by Dimitri Knjazew and published by Springer Science & Business Media. This book was released on 2002-01-31 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this text, Knjazew (SAP AG, Germany) develops a permutation- oriented competent genetic algorithm (GA) and demonstrates its performance and scalability on hard permutation problems. Coverage includes background information about competent GAs; development of the ordering messy genetic algorithm (OmeGA); a detailed scalability and performance analysis of the method; application of the OmeGA to a real world scheduling problem that has been used as a standard benchmark within SAP (a leading German enterprise resource planning software vendor); and suggestions for future research in this area. Requires a basic knowledge of GAs. This book could be used in classes on genetic and evolutionary computation, and in operations research. Annotation copyrighted by Book News Inc., Portland, OR.
Author : Randy L. Haupt
Publisher : John Wiley & Sons
ISBN 13 : 0471671754
Total Pages : 273 pages
Book Rating : 4.4/5 (716 download)
Download or read book Practical Genetic Algorithms written by Randy L. Haupt and published by John Wiley & Sons. This book was released on 2004-07-30 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: * This book deals with the fundamentals of genetic algorithms and their applications in a variety of different areas of engineering and science * Most significant update to the second edition is the MATLAB codes that accompany the text * Provides a thorough discussion of hybrid genetic algorithms * Features more examples than first edition
Author : Melanie Mitchell
Publisher : MIT Press
ISBN 13 : 9780262631853
Total Pages : 226 pages
Book Rating : 4.6/5 (318 download)
Download or read book An Introduction to Genetic Algorithms written by Melanie Mitchell and published by MIT Press. This book was released on 1998-03-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
Author : Das, Raja
Publisher : IGI Global
ISBN 13 : 152252441X
Total Pages : 556 pages
Book Rating : 4.5/5 (225 download)
Download or read book Handbook of Research on Manufacturing Process Modeling and Optimization Strategies written by Das, Raja and published by IGI Global. This book was released on 2017-03-10 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.
Author : Franz Rothlauf
Publisher : Physica
ISBN 13 : 3642880940
Total Pages : 295 pages
Book Rating : 4.6/5 (428 download)
Download or read book Representations for Genetic and Evolutionary Algorithms written by Franz Rothlauf and published by Physica. This book was released on 2012-12-06 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.
Author : David E. Goldberg
Publisher : Springer Science & Business Media
ISBN 13 : 1475736436
Total Pages : 259 pages
Book Rating : 4.4/5 (757 download)
Download or read book The Design of Innovation written by David E. Goldberg and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: 7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Difficulty: Noise 88 Crosstalk: All Roads Lead to the Core 8 89 9 From Multimodality to Hierarchy 93 10 Summary 100 7 ENSURING BUILDING BLOCK SUPPLY 101 1 Past Work 101 2 Facetwise Supply Model I: One BB 102 Facetwise Supply Model II: Partition Success 103 3 4 Population Size for BB Supply 104 Summary 5 106 8 ENSURING BUILDING BLOCK GROWTH 109 1 The Schema Theorem: BB Growth Bound 109 2 Schema Growth Somewhat More Generally 111 3 Designing for BB Market Share Growth 112 4 Selection Press ure for Early Success 114 5 Designing for Late in the Day 116 The Schema Theorem Works 6 118 A Demonstration of Selection Stall 7 119 Summary 122 8 9 MAKING TIME FOR BUILDING BLOCKS 125 1 Analysis of Selection Alone: Takeover Time 126 2 Drift: When Selection Chooses for No Reason 129 3 Convergence Times with Multiple BBs 132 4 A Time-Scales Derivation of Critical Locus 142 5 A Little Model of Noise-Induced Run Elongation 143 6 From Alleles to Building Blocks 147 7 Summary 148 10 DECIDING WELL 151 1 Why is Decision Making a Problem? 151
Author : Gabriel Luque
Publisher : Springer Science & Business Media
ISBN 13 : 3642220835
Total Pages : 173 pages
Book Rating : 4.6/5 (422 download)
Download or read book Parallel Genetic Algorithms written by Gabriel Luque and published by Springer Science & Business Media. This book was released on 2011-06-15 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers can learn how to solve complex tasks by reducing their high computational times. Dealing with two scientific fields (parallelism and GAs) is always difficult, and the book seeks at gracefully introducing from basic concepts to advanced topics. The presentation is structured in three parts. The first one is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. A second part deals with the theory for pGAs, with an eye on theory-to-practice issues. A final third part offers a very wide study of pGAs as practical problem solvers, addressing domains such as natural language processing, circuits design, scheduling, and genomics. This volume will be helpful both for researchers and practitioners. The first part shows pGAs to either beginners and mature researchers looking for a unified view of the two fields: GAs and parallelism. The second part partially solves (and also opens) new investigation lines in theory of pGAs. The third part can be accessed independently for readers interested in applications. The result is an excellent source of information on the state of the art and future developments in parallel GAs.
Author : V. Sivakumar Reddy
Publisher : Springer Nature
ISBN 13 : 9811612498
Total Pages : 663 pages
Book Rating : 4.8/5 (116 download)
Download or read book Soft Computing and Signal Processing written by V. Sivakumar Reddy and published by Springer Nature. This book was released on 2021-07-23 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
Author : Colin Reeves
Publisher : Springer Science & Business Media
ISBN 13 : 1402072406
Total Pages : 337 pages
Book Rating : 4.4/5 (2 download)
Download or read book Genetic Algorithms: Principles and Perspectives written by Colin Reeves and published by Springer Science & Business Media. This book was released on 2002-12-31 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.
Author : Thomas Jansen
Publisher : Springer Science & Business Media
ISBN 13 : 364217339X
Total Pages : 264 pages
Book Rating : 4.6/5 (421 download)
Download or read book Analyzing Evolutionary Algorithms written by Thomas Jansen and published by Springer Science & Business Media. This book was released on 2013-01-24 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Ivan Gridin
Publisher : BPB Publications
ISBN 13 : 8194837758
Total Pages : 330 pages
Book Rating : 4.1/5 (948 download)
Download or read book Learning Genetic Algorithms with Python written by Ivan Gridin and published by BPB Publications. This book was released on 2021-02-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Refuel your AI Models and ML applications with High-Quality Optimization and Search Solutions DESCRIPTION Genetic algorithms are one of the most straightforward and powerful techniques used in machine learning. This book ÔLearning Genetic Algorithms with PythonÕ guides the reader right from the basics of genetic algorithms to its real practical implementation in production environments.Ê Each of the chapters gives the reader an intuitive understanding of each concept. You will learn how to build a genetic algorithm from scratch and implement it in real-life problems. Covered with practical illustrated examples, you will learn to design and choose the best model architecture for the particular tasks. Cutting edge examples like radar and football manager problem statements, you will learn to solve high-dimensional big data challenges with ways of optimizing genetic algorithms. KEY FEATURESÊÊ _ Complete coverage on practical implementation of genetic algorithms. _ Intuitive explanations and visualizations supply theoretical concepts. _ Added examples and use-cases on the performance of genetic algorithms. _ Use of Python libraries and a niche coverage on the performance optimization of genetic algorithms. WHAT YOU WILL LEARNÊ _ Understand the mechanism of genetic algorithms using popular python libraries. _ Learn the principles and architecture of genetic algorithms. _ Apply and Solve planning, scheduling and analytics problems in Enterprise applications. _Ê Expert learning on prime concepts like Selection, Mutation and Crossover. WHO THIS BOOK IS FORÊÊ The book is for Data Science team, Analytics team, AI Engineers, ML Professionals who want to integrate genetic algorithms to refuel their ML and AI applications. No special expertise about machine learning is required although a basic knowledge of Python is expected. TABLE OF CONTENTS 1. Introduction 2. Genetic Algorithm Flow 3. Selection 4. Crossover 5. Mutation 6. Effectiveness 7. Parameter Tuning 8. Black-box Function 9. Combinatorial Optimization: Binary Gene Encoding 10. Combinatorial Optimization: Ordered Gene Encoding 11. Other Common Problems 12. Adaptive Genetic Algorithm 13. Improving Performance
