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Handbook of Optimization
(Englisch)
From Classical to Modern Approach
Zelinka, Ivan & Snasael, Vaclav & Abraham, Ajith

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Handbook of Optimization

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  • Springer Gabler
    in Springer-Verlag GmbH
    Heidelberger Platz 3
    DE-14197 Berlin
Moluna-Artikelnummer
  • 449137387

Produktbeschreibung

Self contained handbook covering the complete field of optimization 

Covers classical as well as the modern approaches 

Written by leading experts


Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.

 


Classical methods - theory.- Classical methods - Applications.- Heuristics - Theory.- Heuristics - Applications.

From the reviews:

"In more than 1,000 pages, the editors of this book have gathered over 40 contributions representing a variety of optimization flavors. ... written as tutorials or transactional papers for scientists working in the area. ... I do believe this book will be useful to experts in optimization who are seeking inspiration, and lecturers searching for examples for graduate or PhD courses.” (Piotr Cholda, Computing Reviews, July, 2013)

This book discusses a wide spectrum of optimization methods from classical to modern, including heuristics. Coverage includes such approaches as game theory, evolutionary algorithms and modeling of evolutionary algorithm dynamics as found in complex networks.

Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.



From the reviews:

"In more than 1,000 pages, the editors of this book have gathered over 40 contributions representing a variety of optimization flavors. ... written as tutorials or transactional papers for scientists working in the area. ... I do believe this book will be useful to experts in optimization who are seeking inspiration, and lecturers searching for examples for graduate or PhD courses." (Piotr Cholda, Computing Reviews, July, 2013)

Inhaltsverzeichnis



Classical methods - theory.- Classical methods - Applications.- Heuristics - Theory.- Heuristics - Applications.


Klappentext

Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks. rn 


Self contained handbook covering the complete field of optimization

rn

Covers classical as well as the modern approaches

rn

Written by leading experts

rn



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