Theory and Principled Methods for the Design of Metaheuristics (Natural Computing Series) - Hardcover
This edited book puts together theoretical and principled methods for incorporating problem knowledge in evolutionary algorithms and other metaheuristics, and for designing and adapting them to the specific problems' features. The first part of the book suggests a line of theoretical enquiry aimed at deriving new search algorithms from "scratch" based on well-formulated assumptions on the class of problems considered. The second part of the book is more pragmatic and presents principled methods to adapt and design search operators to the problem at hand. It also demonstrates how statistical methods and other theory-driven tools can use experimental data to enhance the performance of existing metaheuristics in a systematic way. This includes analysing and simplifying metahueirstics, tuning parameters and building algorithms' portfolio.
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“This is a valuable addition to the literature on heuristics for search. Both practitioners and theoreticians should read it.” (J. P. E. Hodgson, Computing Reviews, July, 2014)
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex.
In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters.
With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.
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- PublisherSpringer
- Publication date2014
- ISBN 10 3642332056
- ISBN 13 9783642332050
- BindingHardcover
- Number of pages290
- EditorBorenstein Yossi, Moraglio Alberto
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Theory and Principled Methods for the Design of Metaheuristics
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Book Description Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence. 292 pp. Englisch. Seller Inventory # 9783642332050
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Theory and Principled Methods for the Design of Metaheuristics
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Book Description Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence. Seller Inventory # 9783642332050
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Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Valuable for practitioners and researchersExplains theoretical basis of key metaheuristic techniquesContributing authors among the leading authorities on the theory of evolutionary computation, search, and heuristicsDr. Yossi . Seller Inventory # 5057191
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