Cellular Genetic Algorithms

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Cellular Genetic Algorithms

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Author : Enrique Alba
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-05

Cellular Genetic Algorithms written by Enrique Alba 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 2009-04-05 with Mathematics categories.

Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice. This book is a key source for studying and designing cellular GAs, as well as a self-contained primary reference book for these algorithms.

Industrial Applications Of Genetic Algorithms

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Author : Charles Karr
language : en
Publisher: CRC Press
Release Date : 1998-12-29

Industrial Applications Of Genetic Algorithms written by Charles Karr and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-29 with Computers categories.

Genetic algorithms (GAs) are computer-based search techniques patterned after the genetic mechanisms of biological organisms that have adapted and flourished in changing, highly competitive environments for millions of years. GAs have been successfully applied to problems in a variety of studies, and their popularity continues to increase because of their effectiveness, applicability, and ease of use. Industrial Applications of Genetic Algorithms shows how GAs have made the leap form their origins in the laboratory to the practicing engineer's toolbox. Each chapter in the book describes a project completed by a graduate student at the University of Alabama.

An Introduction To Genetic Algorithms

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Author : Melanie Mitchell
language : en
Publisher: MIT Press
Release Date : 1998-03-02

An Introduction To Genetic Algorithms written by Melanie Mitchell and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-03-02 with Computers categories.

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.

Evolutionary Algorithms For Mobile Ad Hoc Networks

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Author : Bernabé Dorronsoro
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-08

Evolutionary Algorithms For Mobile Ad Hoc Networks written by Bernabé Dorronsoro 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 2014-04-08 with Computers categories.

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field. Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily research Presents complete and up-to-date surveys on topics like network and mobility simulators Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

Parallel Genetic Algorithms

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Author : Gabriel Luque
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-15

Parallel Genetic Algorithms written by Gabriel Luque 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 2011-06-15 with Computers categories.

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.

Cellular Learning Automata Theory And Applications

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Author : Reza Vafashoar
language : en
Publisher: Springer Nature
Release Date : 2020-07-24

Cellular Learning Automata Theory And Applications written by Reza Vafashoar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-24 with Technology & Engineering categories.

This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments. The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.

Efficient And Accurate Parallel Genetic Algorithms

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Author : Erick Cantú-Paz
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Efficient And Accurate Parallel Genetic Algorithms written by Erick Cantú-Paz 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.

As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm's parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.

Theory Of Practical Cellular Automaton

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Author : Xuewei Li
language : en
Publisher: Springer
Release Date : 2018-05-17

Theory Of Practical Cellular Automaton written by Xuewei Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-17 with Business & Economics categories.

This book addresses the intellectual foundations, function, modeling approaches and complexity of cellular automata; explores cellular automata in combination with genetic algorithms, neural networks and agents; and discusses the applications of cellular automata in economics, traffic and the spread of disease. Pursuing a blended approach between knowledge and philosophy, it assigns equal value to methods and applications.

Cellular Automata

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Author : Samira El Yacoubi
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-19

Cellular Automata written by Samira El Yacoubi 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 2006-09-19 with Computers categories.

This book constitutes the refereed proceedings of the 7th International Conference on Cellular Automata for Research and Industry, ACRI 2006. The book presents 53 revised full papers and 19 revised poster papers together with 6 invited lectures. Topical sections include CA theory and implementation, computational theory, population dynamics, physical modeling, urban, environmental and social modeling, traffic and boolean networks, multi-agents and robotics, as well as crowds and cellular automata, and more.

Genetic Algorithms And Genetic Programming

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Author : Michael Affenzeller
language : en
Publisher: CRC Press
Release Date : 2009-04-09

Genetic Algorithms And Genetic Programming written by Michael Affenzeller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-09 with Computers categories.

Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al