Exploitation of Linkage Learning in Evolutionary Algorithms

Exploitation of Linkage Learning in Evolutionary Algorithms PDF Author: Ying-ping Chen
Publisher: Springer Science & Business Media
ISBN: 3642128343
Category : Technology & Engineering
Languages : en
Pages : 245

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Book Description
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Exploitation of Linkage Learning in Evolutionary Algorithms

Exploitation of Linkage Learning in Evolutionary Algorithms PDF Author: Ying-ping Chen
Publisher: Springer Science & Business Media
ISBN: 3642128343
Category : Technology & Engineering
Languages : en
Pages : 245

Get Book Here

Book Description
One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Genetic and Evolutionary Computation--GECCO 2003

Genetic and Evolutionary Computation--GECCO 2003 PDF Author: Erick Cantú-Paz
Publisher: Springer Science & Business Media
ISBN: 3540406026
Category : Computers
Languages : en
Pages : 1294

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Book Description
The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionaty Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003. The 193 revised full papers and 93 poster papers presented were carefully reviewed and selected from a total of 417 submissions. The papers are organized in topical sections on a-life adaptive behavior, agents, and ant colony optimization; artificial immune systems; coevolution; DNA, molecular, and quantum computing; evolvable hardware; evolutionary robotics; evolution strategies and evolutionary programming; evolutionary sheduling routing; genetic algorithms; genetic programming; learning classifier systems; real-world applications; and search based softare engineering.

Genetic and Evolutionary Computation — GECCO 2004

Genetic and Evolutionary Computation — GECCO 2004 PDF Author: Kalyanmoy Deb
Publisher: Springer Science & Business Media
ISBN: 3540223444
Category : Computers
Languages : en
Pages : 1490

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Book Description
The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.

Introduction to Evolutionary Computing

Introduction to Evolutionary Computing PDF Author: A.E. Eiben
Publisher: Springer Science & Business Media
ISBN: 9783540401841
Category : Computers
Languages : en
Pages : 328

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Book Description
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.

Theoretical Aspects of Evolutionary Computing

Theoretical Aspects of Evolutionary Computing PDF Author: Leila Kallel
Publisher: Springer Science & Business Media
ISBN: 9783540673965
Category : Business & Economics
Languages : en
Pages : 516

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Book Description
This book is the first in the field to provide extensive, entry level tutorials to the theory of Evolutionary Computing, covering the main approaches to understanding the dynamics of Evolutionary Algorithms. It combines this with recent, previously unpublished research papers based on the material of the tutorials. The outcome is a book which is self-contained to a large degree, attractive both to graduate students and researchers from other fields who want to get acquainted with the theory of Evolutionary Computing, and to active researchers in the field who can use this book as a reference and a source of recent results.

Evolutionary Computation in Combinatorial Optimization

Evolutionary Computation in Combinatorial Optimization PDF Author: Jens Gottlieb
Publisher: Springer Science & Business Media
ISBN: 3540253378
Category : Computers
Languages : en
Pages : 282

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Book Description
This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2005, held in Lausanne, Switzerland in March/April 2005. The 24 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers cover evolutionary algorithms as well as related approaches like scatter search, simulated annealing, ant colony optimization, immune algorithms, variable neighborhood search, hyperheuristics, and estimation of distribution algorithms. The papers deal with representations, analysis of operators and fitness landscapes, and comparison algorithms. Among the combinatorial optimization problems studied are graph coloring, quadratic assignment, knapsack, graph matching, packing, scheduling, timetabling, lot-sizing, and the traveling salesman problem.

Linkage in Evolutionary Computation

Linkage in Evolutionary Computation PDF Author: Ying-ping Chen
Publisher: Springer Science & Business Media
ISBN: 3540850678
Category : Computers
Languages : en
Pages : 487

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Book Description
In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily ”fooled” by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Hybrid Evolutionary Algorithms

Hybrid Evolutionary Algorithms PDF Author: Crina Grosan
Publisher: Springer
ISBN: 3540732977
Category : Computers
Languages : en
Pages : 410

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Book Description
This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms". The chapters deal with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. Overall, the book has 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. The contributions were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.

Evolutionary Computation 1

Evolutionary Computation 1 PDF Author: Thomas Baeck
Publisher: CRC Press
ISBN: 1351989421
Category : Mathematics
Languages : en
Pages : 374

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Book Description
The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

Handbook of Statistical Genomics

Handbook of Statistical Genomics PDF Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 1119429250
Category : Science
Languages : en
Pages : 1740

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Book Description
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.