Druck auf Anfrage Neuware - Printed after ordering - Di erential evolution is one of the most recent global optimizers. Discovered in 1995 it rapidly proved its practical e ciency. This book gives you a chance to learn all about di erential evolution. On reading it you will be able to pro tably apply this reliable method to problems in your eld. Asforme,mypassionforintelligentsystemsandoptimizationbeganasfar back as during my studies at Moscow State Technical University of Bauman, the best engineering school in Russia. At that time, I was gathering material for my future thesis. Being interested in my work, the Mining School of Paris proposed that I write a dissertation in France. I hesitated some time over a choice, but my natural curiosity and taste for novelty nally prevailed. At present, Docteur ` es science en informatique de l'EcoledesMinesdeParis,I am concentrating on the development of my own enterprise. If optimization is my vocation, my hobbies are mathematics and music. Although mathematics disciplines the mind, music is lled with emotions. While playing my favorite composition, I decided to write this book. The purpose of the book is to give, in a condensed but overview form, a description of di erential evolution. In addition, this book makes accessible to a wide audience the fruits of my long research in optimization. Namely, I laid the foundation of the universal concept of search strategies design, suitable not only for di erential evolution but for many other algorithms. Also, I introduced a principle of energetic selection, an e cient method of hybridization, and advanced paralleling techniques.

Bestandsnummer des Verk�ufers 9780387368955

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Bibliografische Details

Titel: Differential Evolution : In Search of Solutions
Verlag: Springer US, Springer US
Erscheinungsjahr: 2006
Sprache: Englisch
ISBN-10: 0387368957
ISBN-13: 9780387368955
Einband: Buch
Zustand: Neu

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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.

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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

Audience

Differential Evolution will be of interest to students, teachers, engineers, and researchers from various fields, including computer science, applied mathematics, optimization and operations research, artificial evolution and evolutionary algorithms, telecommunications, engineering design, bioinformatics and computational chemistry, chemical engineering, mechanical engineering, electrical engineering, and physics.

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