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  • Format: PDF


The human being aspires to the best possible performance. Both individuals and enterprises are looking for optimal - in other words, the best possible - solutions for situations or problems they face. Most of these problems can be expressed in mathematical terms, and so the methods of optimization undoubtedly render a significant aid. In cases where there are many local optima; intricate constraints; mixed-type variables; or noisy, time-dependent or otherwise ill-defined functions, the usual methods don't give satisfactory results. Are you seeking fresh ideas or more efficient methods, or do…mehr

Produktbeschreibung
The human being aspires to the best possible performance. Both individuals and enterprises are looking for optimal - in other words, the best possible - solutions for situations or problems they face. Most of these problems can be expressed in mathematical terms, and so the methods of optimization undoubtedly render a significant aid. In cases where there are many local optima; intricate constraints; mixed-type variables; or noisy, time-dependent or otherwise ill-defined functions, the usual methods don't give satisfactory results. Are you seeking fresh ideas or more efficient methods, or do you perhaps want to be well-informed about the latest achievements in optimization? If so, this book is for you. This book develops a unified insight on population-based optimization through Differential Evolution, one of the most recent and efficient optimization algorithms. You will find, in this book, everything concerning Differential Evolution and its application in its newest formulation. This book will be a valuable source of information for a very large readership, including researchers, students and practitioners. The text may be used in a variety of optimization courses as well. Features include: Neoteric view of Differential Evolution; Unique formula of global optimization; The best known metaheuristics through the prism of Differential Evolution; Revolutionary ideas in population-based optimization. TOC:Preface.- 1. Differential Evolution.- 2. Neoteric Differential Evolution.- 3. Strategies of Search.- 4. Exploration and Exploitation.- 5. New Performance Measures.- 6. Transversal Differential Evolution.- 7. On Analogy with Some Other Algorithms.- 8. Energetic Selection Principle.- 9. On Hybridization of Differential Evolution.- 10. Applications.- 11. End Notes.- A. Famous Differential Evolution.- B. Intelligent Selection Rules.- C. Standard Test Suite.- D. Coordinate Rotation of a Test Function.- E. Practical Guidelines to Application.- References.- Index.

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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Erscheinungstermin: 15.02.2007
  • Englisch
  • ISBN-13: 9780387368962
  • Artikelnr.: 37287859
Autorenporträt
Vitaliy Feoktistov, Nimes, France
Inhaltsangabe
Differential Evolution.- Neoteric Differential Evolution.- Strategies of Search.- Exploration and Exploitation.- New Performance Measures.- Transversal Differential Evolution.- On Analogy with Some Other Algorithms.- Energetic Selection Principle.- On Hybridization of Differential Evolution.- Applications.- End Notes.
Rezensionen
From the reviews: "The book covers almost everything, including the latest developments, about the evolutionary meta-heuristic approach. ... a well-written book which is enriched by the interesting writing style of the author. ... The author is not only an expert in the field of the book, but also has had a great impact on its latest developments ... . the stress of the book lies more on the practical side of the algorithm than on its theory, it is a good source for academia, science and especially practice." (Panos M. Pardalos, Mathematical Reviews, Issue 2007 e) "The book deals with the neoteric differential evolution, strategies of search, transversal differential evolution, energetic selection principle, hybridization of differential evolution and applications. The writing style is very dynamic and nice, inviting the interested reader (students, teachers, engineers etc.) to learn more about this exciting subject." (Florin Gorunescu, Zentralblatt MATH, Vol. 1136 (14), 2008)