Cellular Genetic Algorithms

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Publisher : Springer Science & Business Media
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ISBN 10 : 9780387776101
Pages : 248 pages
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Rating : 4.7/5 (776 users download)


Download Cellular Genetic Algorithms by Enrique Alba PDF/Ebook Free clicking on the below button will initiate the downloading process of Cellular Genetic Algorithms by Enrique Alba. This book is available in ePub and PDF format with a single click unlimited downloads. 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.


Theory of Practical Cellular Automaton

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Publisher : Springer
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ISBN 10 : 9789811074974
Pages : 352 pages
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Rating : 4.7/5 (74 users download)


Download Theory of Practical Cellular Automaton by Xuewei Li PDF/Ebook Free clicking on the below button will initiate the downloading process of Theory of Practical Cellular Automaton by Xuewei Li. This book is available in ePub and PDF format with a single click unlimited downloads. 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.


Image Approximation Via a Cellular Genetic Algorithm with Element List Encoding and Gaussian Neighborhood Topology

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ISBN 10 : OCLC:664906303
Pages : 138 pages
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Download Image Approximation Via a Cellular Genetic Algorithm with Element List Encoding and Gaussian Neighborhood Topology by Joshua Alto PDF/Ebook Free clicking on the below button will initiate the downloading process of Image Approximation Via a Cellular Genetic Algorithm with Element List Encoding and Gaussian Neighborhood Topology by Joshua Alto. This book is available in ePub and PDF format with a single click unlimited downloads. "Image approximation with finite quantities of polygons is an optimization problem with many local optima. Such problems may be well suited to evolutionary algorithms (EAs). Work done on this problem has focused on genetic programming (GP) employing a (1+1)- Evolutionary Strategy (ES). explore solving the problem with a particular genetic algorithm (GA). There are many different factors to decide upon in designing a GA including: encoding of the problem, panmictic vs. cellular/local populations and neighborhood size for non-panmictic populations. The encoding of a problem in a GA is an important consideration which influences the effect of mutation and crossover. Local evolution such as cellular evolutionary algorithms attempt to prevent the premature convergence to a local optima often found in panmictic algorithms to optimize the exploration/exploitation trade- off. Neighborhoods in cellular evolutionary algorithms are typically statically defined in size for a given problem; either using a static shape, or a static length random walk. This paper proposes a dynamic-sized element-list type encoding for a cellular evolutionary algorithm with a clipped dynamic Gaussian Euclidean ranged neighborhood to determine if it can solve this type of problem better than existing solutions. I find that this GA greatly outperforms the seminal implementation, Alsing-EvoLisa, when compared with equal numbers of generations. However, it is in turn greatly outperformed by Alsing-EvoLisa when compared with equal numbers of evaluations. Therefore the success of this algorithm will depend on the degree to which it can be parallelized. I further find that the selective pressure of this algorithm, with the tested parameter values, is lower than optimal for this problem and the selected targets"--Document.


Dynamic and Fault Tolerant Three-dimensional Cellular Genetic Algorithms

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ISBN 10 : OCLC:862754861
Pages : pages
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Download Dynamic and Fault Tolerant Three-dimensional Cellular Genetic Algorithms by Asmaa Al Naqi PDF/Ebook Free clicking on the below button will initiate the downloading process of Dynamic and Fault Tolerant Three-dimensional Cellular Genetic Algorithms by Asmaa Al Naqi. This book is available in ePub and PDF format with a single click unlimited downloads.


Efficient and Accurate Parallel Genetic Algorithms

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Publisher : Springer Science & Business Media
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ISBN 10 : 9781461543695
Pages : 162 pages
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Rating : 4.4/5 (543 users download)


Download Efficient and Accurate Parallel Genetic Algorithms by Erick Cantú-Paz PDF/Ebook Free clicking on the below button will initiate the downloading process of Efficient and Accurate Parallel Genetic Algorithms by Erick Cantú-Paz. This book is available in ePub and PDF format with a single click unlimited downloads. 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.


Design of Virtual Cellular Manufacturing Systems Using Genetic Algorithms

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Publisher : Open Dissertation Press
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ISBN 10 : 1374690570
Pages : pages
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Rating : 4.7/5 (374 users download)


Download Design of Virtual Cellular Manufacturing Systems Using Genetic Algorithms by 王曉曦 PDF/Ebook Free clicking on the below button will initiate the downloading process of Design of Virtual Cellular Manufacturing Systems Using Genetic Algorithms by 王曉曦. This book is available in ePub and PDF format with a single click unlimited downloads. This dissertation, "Design of Virtual Cellular Manufacturing Systems Using Genetic Algorithms" by 王曉曦, Xiaoxi, Wang, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4257730 Subjects: Manufacturing cells Production scheduling - Mathematical models Algorithms System design


A Representation of Investor Learning Behavior Through Cellular Genetic Algorithms

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ISBN 10 : OCLC:992933448
Pages : pages
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Download A Representation of Investor Learning Behavior Through Cellular Genetic Algorithms by Alvaro Peredo Centellas PDF/Ebook Free clicking on the below button will initiate the downloading process of A Representation of Investor Learning Behavior Through Cellular Genetic Algorithms by Alvaro Peredo Centellas. This book is available in ePub and PDF format with a single click unlimited downloads. This paper implements a Cellular Genetic Algorithm (CGA) to compare key statistics on the earnings of a population of investors with different learning and innovation rates, defined as crossover and mutation rate, respectively. The data used was the adjusted closing price for the S&P Index 500, INX, from two low volatility periods-from 2004 to 2007, and from 2014 to 2017- and a relatively high volatility period-from 2008 to 2011-. This study concluded that there exists a significant difference when investors learn from performing peers and that optimal learning rates may vary between high and low volatility periods, being particularly beneficial in the former ones.


Parallel Genetic Algorithms

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Publisher : Springer Science & Business Media
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ISBN 10 : 9783642220838
Pages : 172 pages
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Rating : 4.2/5 (22 users download)


Download Parallel Genetic Algorithms by Gabriel Luque PDF/Ebook Free clicking on the below button will initiate the downloading process of Parallel Genetic Algorithms by Gabriel Luque. This book is available in ePub and PDF format with a single click unlimited downloads. 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.


Spatially Structured Evolutionary Algorithms

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Publisher : Springer Science & Business Media
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ISBN 10 : 9783540299387
Pages : 193 pages
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Rating : 4.9/5 (299 users download)


Download Spatially Structured Evolutionary Algorithms by Marco Tomassini PDF/Ebook Free clicking on the below button will initiate the downloading process of Spatially Structured Evolutionary Algorithms by Marco Tomassini. This book is available in ePub and PDF format with a single click unlimited downloads. Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks. The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role.


Evolutionary Computation in Combinatorial Optimization

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Publisher : Springer Science & Business Media
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ISBN 10 : 9783540331780
Pages : 292 pages
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Rating : 4.3/5 (331 users download)


Download Evolutionary Computation in Combinatorial Optimization by Jens Gottlieb PDF/Ebook Free clicking on the below button will initiate the downloading process of Evolutionary Computation in Combinatorial Optimization by Jens Gottlieb. This book is available in ePub and PDF format with a single click unlimited downloads. This book constitutes the refereed proceedings of the 6th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2006, held in Budapest, Hungary in April 2006. The 24 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers include coverage of evolutionary algorithms as well as various other metaheuristics, like scatter search, tabu search, and memetic algorithms.


Genetic Algorithms Appled to Cellular Call Admission Problem

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ISBN 10 : OCLC:858923651
Pages : pages
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Download Genetic Algorithms Appled to Cellular Call Admission Problem by A. Yener PDF/Ebook Free clicking on the below button will initiate the downloading process of Genetic Algorithms Appled to Cellular Call Admission Problem by A. Yener. This book is available in ePub and PDF format with a single click unlimited downloads.


Recent Advances in Simulated Evolution and Learning

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Publisher : World Scientific
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ISBN 10 : 9789812561794
Pages : 832 pages
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Rating : 4.6/5 (561 users download)


Download Recent Advances in Simulated Evolution and Learning by K. C. Tan PDF/Ebook Free clicking on the below button will initiate the downloading process of Recent Advances in Simulated Evolution and Learning by K. C. Tan. This book is available in ePub and PDF format with a single click unlimited downloads. Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems. This book has been selected for coverage in: . OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences. Sample Chapter(s). Chapter 1: Co-Evolutionary Learning in Strategic Environments (231 KB). Contents: Evolutionary Theory: Using Evolution to Learn User Preferences (S Ujjin & P J Bentley); Evolutionary Learning Strategies for Artificial Life Characters (M L Netto et al.); The Influence of Stochastic Quality Functions on Evolutionary Search (B Sendhoff et al.); A Real-Coded Cellular Genetic Algorithm Inspired by PredatorOCoPrey Interactions (X Li & S Sutherland); Automatic Modularization with Speciated Neural Network Ensemble (V R Khare & X Yao); Evolutionary Applications: Image Classification using Particle Swarm Optimization (M G Omran et al.); Evolution of Fuzzy Rule Based Controllers for Dynamic Environments (J Riley & V Ciesielski); A Genetic Algorithm for Joint Optimization of Spare Capacity and Delay in Self-Healing Network (S Kwong & H W Chong); Joint Attention in the Mimetic Context OCo What is a OC Mimetic SameOCO? (T Shiose et al.); Time Series Forecast with Elman Neural Networks and Genetic Algorithms (L X Xu et al.); and other articles. Readership: Upper level undergraduates, graduate students, academics, researchers and industrialists in artificial intelligence, evolutionary computation, fuzzy logic and neural networks."


Optimisation of Cellular Manufacturing Systems Using Genetic Algorithms

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ISBN 10 : OCLC:926813825
Pages : pages
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Download Optimisation of Cellular Manufacturing Systems Using Genetic Algorithms by PDF/Ebook Free clicking on the below button will initiate the downloading process of Optimisation of Cellular Manufacturing Systems Using Genetic Algorithms by . This book is available in ePub and PDF format with a single click unlimited downloads.


The Nonlinear Workbook

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Publisher : World Scientific Publishing Company
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ISBN 10 : 9789814583497
Pages : 684 pages
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Rating : 4.8/5 (583 users download)


Download The Nonlinear Workbook by Willi-Hans Steeb PDF/Ebook Free clicking on the below button will initiate the downloading process of The Nonlinear Workbook by Willi-Hans Steeb. This book is available in ePub and PDF format with a single click unlimited downloads. The Nonlinear Workbook provides a comprehensive treatment of all the techniques in nonlinear dynamics together with C++, Java and SymbolicC++ implementations. The book not only covers the theoretical aspects of the topics but also provides the practical tools. To understand the material, more than 100 worked out examples and 160 ready to run programs are included. Each chapter provides a collection of interesting problems. New topics added to the 6th edition are Swarm Intelligence, Quantum Cellular Automata, Hidden Markov Model and DNA, Birkhoff's ergodic theorem and chaotic maps, Banach fixed point theorem and applications, tau-wavelets of Haar, Boolean derivatives and applications, and Cartan forms and Lagrangian. Request Inspection Copy


Genetic Algorithms and Genetic Programming

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Publisher : CRC Press
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ISBN 10 : 1420011324
Pages : 379 pages
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Rating : 4.2/5 (42 users download)


Download Genetic Algorithms and Genetic Programming by Michael Affenzeller PDF/Ebook Free clicking on the below button will initiate the downloading process of Genetic Algorithms and Genetic Programming by Michael Affenzeller. This book is available in ePub and PDF format with a single click unlimited downloads. 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 algorithm development. The book focuses on both theoretical and empirical aspects. The theoretical sections explore the important and characteristic properties of the basic GA as well as main characteristics of the selected algorithmic extensions developed by the authors. In the empirical parts of the text, the authors apply GAs to two combinatorial optimization problems: the traveling salesman and capacitated vehicle routing problems. To highlight the properties of the algorithmic measures in the field of GP, they analyze GP-based nonlinear structure identification applied to time series and classification problems. Written by core members of the HeuristicLab team, this book provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts. By comparing the results of standard GA and GP implementation with several algorithmic extensions, it also shows how to substantially increase achievable solution quality.


Parameter Setting in Evolutionary Algorithms

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Publisher : Springer Science & Business Media
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ISBN 10 : 9783540694311
Pages : 318 pages
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Rating : 4.9/5 (694 users download)


Download Parameter Setting in Evolutionary Algorithms by F.J. Lobo PDF/Ebook Free clicking on the below button will initiate the downloading process of Parameter Setting in Evolutionary Algorithms by F.J. Lobo. This book is available in ePub and PDF format with a single click unlimited downloads. One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.


Simulated Evolution and Learning

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Publisher : Springer Science & Business Media
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ISBN 10 : 9783540896937
Pages : 658 pages
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Rating : 4.9/5 (896 users download)


Download Simulated Evolution and Learning by Xiaodong Li PDF/Ebook Free clicking on the below button will initiate the downloading process of Simulated Evolution and Learning by Xiaodong Li. This book is available in ePub and PDF format with a single click unlimited downloads. This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.