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Differential Evolution

2006-03-04 Mathematics
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Release : 2006-03-04
Genre : Mathematics
Kind : eBook
Book Rating : 060/5 ( reviews)

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Book Synopsis Differential Evolution by : Kenneth Price

Download or read book Differential Evolution written by Kenneth Price. This book was released on 2006-03-04. Available in PDF, EPUB and Kindle. Book excerpt: Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables. The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores DE in both principle and practice. It is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.

Differential Evolution

2007-02-15 Mathematics
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Release : 2007-02-15
Genre : Mathematics
Kind : eBook
Book Rating : 965/5 ( reviews)

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Book Synopsis Differential Evolution by : Vitaliy Feoktistov

Download or read book Differential Evolution written by Vitaliy Feoktistov. This book was released on 2007-02-15. Available in PDF, EPUB and Kindle. Book excerpt: Individuals and enterprises are looking for optimal solutions for the problems they face. Most problems can be expressed in mathematical terms, and so the methods of optimization render a significant aid. This book details the latest achievements in optimization. It offers comprehensive coverage on Differential Evolution, presenting revolutionary ideas in population-based optimization and shows the best known metaheuristics through the prism of Differential Evolution.

Adaptive Differential Evolution

2009-07-09 Mathematics
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Release : 2009-07-09
Genre : Mathematics
Kind : eBook
Book Rating : 271/5 ( reviews)

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Book Synopsis Adaptive Differential Evolution by : Jingqiao Zhang

Download or read book Adaptive Differential Evolution written by Jingqiao Zhang. This book was released on 2009-07-09. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental theme of this book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. The book offers real-world insights into a variety of large-scale complex industrial applications.

Advances in Differential Evolution

2008-07-23 Computers
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Release : 2008-07-23
Genre : Computers
Kind : eBook
Book Rating : 277/5 ( reviews)

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Book Synopsis Advances in Differential Evolution by : Uday K. Chakraborty

Download or read book Advances in Differential Evolution written by Uday K. Chakraborty. This book was released on 2008-07-23. Available in PDF, EPUB and Kindle. Book excerpt: Differential evolution is arguably one of the hottest topics in today's computational intelligence research. This book seeks to present a comprehensive study of the state of the art in this technology and also directions for future research. The fourteen chapters of this book have been written by leading experts in the area. The first seven chapters focus on algorithm design, while the last seven describe real-world applications. Chapter 1 introduces the basic differential evolution (DE) algorithm and presents a broad overview of the field. Chapter 2 presents a new, rotationally invariant DE algorithm. The role of self-adaptive control parameters in DE is investigated in Chapter 3. Chapters 4 and 5 address constrained optimization; the former develops suitable stopping conditions for the DE run, and the latter presents an improved DE algorithm for problems with very small feasible regions. A novel DE algorithm, based on the concept of "opposite" points, is the topic of Chapter 6. Chapter 7 provides a survey of multi-objective differential evolution algorithms. A review of the major application areas of differential evolution is presented in Chapter 8. Chapter 9 discusses the application of differential evolution in two important areas of applied electromagnetics. Chapters 10 and 11 focus on applications of hybrid DE algorithms to problems in power system optimization. Chapter 12 applies the DE algorithm to computer chess. The use of DE to solve a problem in bioprocess engineering is discussed in Chapter 13. Chapter 14 describes the application of hybrid differential evolution to a problem in control engineering.

Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization

2008-12-23 Technology & Engineering
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Release : 2008-12-23
Genre : Technology & Engineering
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Book Rating : 516/5 ( reviews)

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Book Synopsis Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization by : Godfrey C. Onwubolu

Download or read book Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization written by Godfrey C. Onwubolu. This book was released on 2008-12-23. Available in PDF, EPUB and Kindle. Book excerpt: What is combinatorial optimization? Traditionally, a problem is considered to be c- binatorial if its set of feasible solutions is both ?nite and discrete, i. e. , enumerable. For example, the traveling salesman problem asks in what order a salesman should visit the cities in his territory if he wants to minimize his total mileage (see Sect. 2. 2. 2). The traveling salesman problem’s feasible solutions - permutations of city labels - c- prise a ?nite, discrete set. By contrast, Differential Evolution was originally designed to optimize functions de?ned on real spaces. Unlike combinatorial problems, the set of feasible solutions for real parameter optimization is continuous. Although Differential Evolution operates internally with ?oating-point precision, it has been applied with success to many numerical optimization problems that have t- ditionally been classi?ed as combinatorial because their feasible sets are discrete. For example, the knapsack problem’s goal is to pack objects of differing weight and value so that the knapsack’s total weight is less than a given maximum and the value of the items inside is maximized (see Sect. 2. 2. 1). The set of feasible solutions - vectors whose components are nonnegative integers - is both numerical and discrete. To handle such problems while retaining full precision, Differential Evolution copies ?oating-point - lutions to a temporary vector that, prior to being evaluated, is truncated to the nearest feasible solution, e. g. , by rounding the temporary parameters to the nearest nonnegative integer.

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