Parallel Evolutionary Computations

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Efficient and Accurate Parallel Genetic Algorithms

Author : Erick Cantú-Paz
Publisher : Springer Science & Business Media
ISBN 13 : 9780792372219
Total Pages : 192 pages
Book Rating : 4.3/5 (722 download)

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Book Synopsis Efficient and Accurate Parallel Genetic Algorithms by : Erick Cantú-Paz

Download or read book Efficient and Accurate Parallel Genetic Algorithms written by Erick Cantú-Paz and published by Springer Science & Business Media. This book was released on 2000-11-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Parallel Genetic Algorithms

Author : Gabriel Luque
Publisher : Springer Science & Business Media
ISBN 13 : 3642220835
Total Pages : 173 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Parallel Genetic Algorithms by : Gabriel Luque

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.

Parallel Evolutionary Computations

Author : Enrique Alba
Publisher : Springer
ISBN 13 : 3540328394
Total Pages : 213 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Parallel Evolutionary Computations by : Enrique Alba

Download or read book Parallel Evolutionary Computations written by Enrique Alba and published by Springer. This book was released on 2006-08-29 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and parallel hardware implementations, as well as on their impact on several applications. It offers a wide spectrum of sample works developed in leading research about parallel implementations of efficient techniques at the heart of computational intelligence.

Springer Handbook of Computational Intelligence

Author : Janusz Kacprzyk
Publisher : Springer
ISBN 13 : 3662435055
Total Pages : 1637 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Springer Handbook of Computational Intelligence by : Janusz Kacprzyk

Download or read book Springer Handbook of Computational Intelligence written by Janusz Kacprzyk and published by Springer. This book was released on 2015-05-28 with total page 1637 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Evolutionary Algorithms for Solving Multi-Objective Problems

Author : Carlos Coello Coello
Publisher : Springer Science & Business Media
ISBN 13 : 0387367977
Total Pages : 810 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello

Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Massively Parallel Evolutionary Computation on GPGPUs

Author : Shigeyoshi Tsutsui
Publisher : Springer Science & Business Media
ISBN 13 : 3642379591
Total Pages : 454 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Massively Parallel Evolutionary Computation on GPGPUs by : Shigeyoshi Tsutsui

Download or read book Massively Parallel Evolutionary Computation on GPGPUs written by Shigeyoshi Tsutsui and published by Springer Science & Business Media. This book was released on 2013-12-05 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have opened up this possibility for parallel EAs, and this is the first book dedicated to this exciting development. The three chapters of Part I are tutorials, representing a comprehensive introduction to the approach, explaining the characteristics of the hardware used, and presenting a representative project to develop a platform for automatic parallelization of evolutionary computing (EC) on GPGPUs. The 10 chapters in Part II focus on how to consider key EC approaches in the light of this advanced computational technique, in particular addressing generic local search, tabu search, genetic algorithms, differential evolution, swarm optimization, ant colony optimization, systolic genetic search, genetic programming, and multiobjective optimization. The 6 chapters in Part III present successful results from real-world problems in data mining, bioinformatics, drug discovery, crystallography, artificial chemistries, and sudoku. Although the parallelism of EAs is suited to the single-instruction multiple-data (SIMD)-based GPU, there are many issues to be resolved in design and implementation, and a key feature of the contributions is the practical engineering advice offered. This book will be of value to researchers, practitioners, and graduate students in the areas of evolutionary computation and scientific computing.

Evolutionary Computation

Author : D. Dumitrescu
Publisher : CRC Press
ISBN 13 : 9780849305887
Total Pages : 424 pages
Book Rating : 4.3/5 (58 download)

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Book Synopsis Evolutionary Computation by : D. Dumitrescu

Download or read book Evolutionary Computation written by D. Dumitrescu and published by CRC Press. This book was released on 2000-06-22 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.

Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation

Author : Samuelson Hong, Wei-Chiang
Publisher : IGI Global
ISBN 13 : 1466636297
Total Pages : 357 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation by : Samuelson Hong, Wei-Chiang

Download or read book Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation written by Samuelson Hong, Wei-Chiang and published by IGI Global. This book was released on 2013-03-31 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Theory of Evolutionary Computation

Author : Benjamin Doerr
Publisher : Springer Nature
ISBN 13 : 3030294145
Total Pages : 527 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Theory of Evolutionary Computation by : Benjamin Doerr

Download or read book Theory of Evolutionary Computation written by Benjamin Doerr and published by Springer Nature. This book was released on 2019-11-20 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Evolution of Parallel Cellular Machines

Author : Moshe Sipper
Publisher : Lecture Notes in Computer Science
ISBN 13 :
Total Pages : 222 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Evolution of Parallel Cellular Machines by : Moshe Sipper

Download or read book Evolution of Parallel Cellular Machines written by Moshe Sipper and published by Lecture Notes in Computer Science. This book was released on 1997-03-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collective systems, abounding in nature, have evolved by natural selection to exhibit striking problem-solving capacities. Employing simple yet versatile parallel cellular models, coupled with evolutionary computation techniques, this volume explores the issue of constructing man-made systems that exhibit characteristics like those occuring in nature. Parallel cellular machines hold potential both scientifically, as vehicles for studying phenomena of interest in areas such as complex adaptive systems and artificial life, and practically, enabling the construction of novel systems, endowed with evolutionary, reproductive, regenerative, and learning capabilities. This volume examines the behavior of such machines, the complex computation they exhibit, and the application of artificial evolution to attain such systems.

Introduction to Evolutionary Computing

Author : A.E. Eiben
Publisher : Springer Science & Business Media
ISBN 13 : 9783540401841
Total Pages : 328 pages
Book Rating : 4.4/5 (18 download)

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Book Synopsis Introduction to Evolutionary Computing by : A.E. Eiben

Download or read book Introduction to Evolutionary Computing written by A.E. Eiben and published by Springer Science & Business Media. This book was released on 2007-08-06 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Master Algorithm

Author : Pedro Domingos
Publisher : Basic Books
ISBN 13 : 0465061923
Total Pages : 354 pages
Book Rating : 4.4/5 (65 download)

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Book Synopsis The Master Algorithm by : Pedro Domingos

Download or read book The Master Algorithm written by Pedro Domingos and published by Basic Books. This book was released on 2015-09-22 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

The Nature of Code

Author : Daniel Shiffman
Publisher : No Starch Press
ISBN 13 : 1718503717
Total Pages : 642 pages
Book Rating : 4.7/5 (185 download)

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Book Synopsis The Nature of Code by : Daniel Shiffman

Download or read book The Nature of Code written by Daniel Shiffman and published by No Starch Press. This book was released on 2024-09-03 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with “The Coding Train” YouTube star Daniel Shiffman. What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. Embark on this extraordinary adventure with projects involving: A physics engine: Simulate the push and pull of gravitational attraction. Flocking birds: Choreograph the mesmerizing dance of a flock. Branching trees: Grow lifelike and organic tree structures. Neural networks: Craft intelligent systems that learn and adapt. Cellular automata: Uncover the magic of self-organizing patterns. Evolutionary algorithms: Play witness to natural selection in your code. Shiffman’s work has transformed thousands of curious minds into creators, breaking down barriers between science, art, and technology, and inviting readers to see code not just as a tool for tasks but as a canvas for boundless creativity. Whether you’re deciphering the elegant patterns of natural phenomena or crafting your own digital ecosystems, Shiffman’s guidance is sure to inform and inspire. The Nature of Code is not just about coding; it’s about looking at the natural world in a new way and letting its wonders inspire your next creation. Dive in and discover the joy of turning code into art—all while mastering coding fundamentals along the way. NOTE: All examples are written with p5.js, a JavaScript library for creative coding, and are available on the book's website.

Evolutionary Computation in Dynamic and Uncertain Environments

Author : Shengxiang Yang
Publisher : Springer
ISBN 13 : 3540497749
Total Pages : 614 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Evolutionary Computation in Dynamic and Uncertain Environments by : Shengxiang Yang

Download or read book Evolutionary Computation in Dynamic and Uncertain Environments written by Shengxiang Yang and published by Springer. This book was released on 2007-04-03 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Evolutionary Computation in Combinatorial Optimization

Author : Peter Merz
Publisher : Springer Science & Business Media
ISBN 13 : 3642203639
Total Pages : 274 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Evolutionary Computation in Combinatorial Optimization by : Peter Merz

Download or read book Evolutionary Computation in Combinatorial Optimization written by Peter Merz and published by Springer Science & Business Media. This book was released on 2011-04-19 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2011, held in Torino, Italy, in April 2011. The 22 revised full papers presented were carefully reviewed and selected from 42 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization.

Evolution as Computation

Author : Laura F. Landweber
Publisher : Springer Science & Business Media
ISBN 13 : 364255606X
Total Pages : 348 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Evolution as Computation by : Laura F. Landweber

Download or read book Evolution as Computation written by Laura F. Landweber and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms and genetic and evolutionary programming.

Parallel Metaheuristics

Author : Enrique Alba
Publisher : John Wiley & Sons
ISBN 13 : 0471739375
Total Pages : 574 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Parallel Metaheuristics by : Enrique Alba

Download or read book Parallel Metaheuristics written by Enrique Alba and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an Introduction to Metaheuristic Techniques, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general.