Spatially Structured Evolutionary Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 3540241930
Total Pages : 200 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Spatially Structured Evolutionary Algorithms by : Marco Tomassini

Download or read book Spatially Structured Evolutionary Algorithms written by Marco Tomassini and published by Springer Science & Business Media. This book was released on 2005-09-27 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Spatially Structured Evolutionary Algorithms

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3540299386
Total Pages : 200 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Spatially Structured Evolutionary Algorithms by : Marco Tomassini

Download or read book Spatially Structured Evolutionary Algorithms written by Marco Tomassini and published by Springer Science & Business Media. This book was released on 2005-12-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Spatial Evolutionary Modeling

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Publisher : Oxford University Press on Demand
ISBN 13 : 0195135687
Total Pages : 265 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Spatial Evolutionary Modeling by : Roman Krzanowski

Download or read book Spatial Evolutionary Modeling written by Roman Krzanowski and published by Oxford University Press on Demand. This book was released on 2001 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary models (e.g., genetic algorithms, artificial life), explored in other fields for the past two decades, are now emerging as an important new tool in GIS for a number of reasons. First, they are highly appropriate for modeling geographic phenomena. Secondly, geographical problems are often spatially separate (broken down into local or regional problems) and evolutionary algorithms can exploit this structure. Finally, the ability to store, manipulate, and visualize spatial data has increased to the point that space-time-attribute databases can be easily handled.

Evolutionary Computation for Modeling and Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 0387319093
Total Pages : 578 pages
Book Rating : 4.94/5 ( download)

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Book Synopsis Evolutionary Computation for Modeling and Optimization by : Daniel Ashlock

Download or read book Evolutionary Computation for Modeling and Optimization written by Daniel Ashlock and published by Springer Science & Business Media. This book was released on 2006-04-04 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Evolutionary Computation and Complex Networks

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Publisher : Springer
ISBN 13 : 3319600001
Total Pages : 148 pages
Book Rating : 4.00/5 ( download)

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Book Synopsis Evolutionary Computation and Complex Networks by : Jing Liu

Download or read book Evolutionary Computation and Complex Networks written by Jing Liu and published by Springer. This book was released on 2018-09-22 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the linkage between evolutionary computation and complex networks and the advantages of cross-fertilising ideas from both fields. Instead of introducing each field individually, the authors focus on the research that sits at the interface of both fields. The book is structured to address two questions: (1) how complex networks are used to analyze and improve the performance of evolutionary computation methods? (2) how evolutionary computation methods are used to solve problems in complex networks? The authors interweave complex networks and evolutionary computing, using evolutionary computation to discover community structure, while also using network analysis techniques to analyze the performance of evolutionary algorithms. The book is suitable for both beginners and senior researchers in the fields of evolutionary computation and complex networks.

Evolutionary Algorithms for Solving Multi-Objective Problems

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Publisher : Springer Science & Business Media
ISBN 13 : 1475751842
Total Pages : 600 pages
Book Rating : 4.40/5 ( 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 2013-03-09 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.

Evolutionary Algorithms in Engineering Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3662034239
Total Pages : 561 pages
Book Rating : 4.31/5 ( download)

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Book Synopsis Evolutionary Algorithms in Engineering Applications by : Dipankar Dasgupta

Download or read book Evolutionary Algorithms in Engineering Applications written by Dipankar Dasgupta and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

Advances in Evolutionary Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 3642189652
Total Pages : 1001 pages
Book Rating : 4.54/5 ( download)

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Book Synopsis Advances in Evolutionary Computing by : Ashish Ghosh

Download or read book Advances in Evolutionary Computing written by Ashish Ghosh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.

Simulated Evolution and Learning

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Publisher : Springer Science & Business Media
ISBN 13 : 3540473319
Total Pages : 960 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Simulated Evolution and Learning by : Tzai-Der Wang

Download or read book Simulated Evolution and Learning written by Tzai-Der Wang and published by Springer Science & Business Media. This book was released on 2006-10-06 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions.

Parallel Problem Solving from Nature-PPSN VI

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Publisher : Springer Science & Business Media
ISBN 13 : 3540410562
Total Pages : 920 pages
Book Rating : 4.60/5 ( download)

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Book Synopsis Parallel Problem Solving from Nature-PPSN VI by : Marc Schoenauer

Download or read book Parallel Problem Solving from Nature-PPSN VI written by Marc Schoenauer and published by Springer Science & Business Media. This book was released on 2000-09-06 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Parallel Problem Solving from Nature, PPSN VI, held in Paris, France in September 2000. The 87 revised full papers presented together with two invited papers were carefully reviewed and selected from 168 submissions. The presentations are organized in topical sections on analysis and theory of evolutionary algorithms, genetic programming, scheduling, representations and operators, co-evolution, constraint handling techniques, noisy and non-stationary environments, combinatorial optimization, applications, machine learning and classifier systems, new algorithms and metaphors, and multiobjective optimization.