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Practical Methods of Optimization de R. Fletcher

Practical Methods of Optimization

Autor R. Fletcher
en Limba Engleză Paperback – 26 iul 2000
Jetzt als preiswerte Paperback-Ausgabe! Das vielfach bewhrte Lehrbuch konzentriert sich auf Optimierungsmethoden, die von praktischem Interesse sind. Lineare und quadratische Programmierung, Newton- und Gradientenmethoden werden ausfhrlich abgehandelt, Optimierungsbedingungen und die Bedeutung von Lagrange-Multiplikatoren werden besprochen. Beschrieben und analysiert wird auch eine Reihe moderner nichtlinearer Verfahren, darunter BFGS und SPQ. (08/00)
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Specificații

ISBN-13: 9780471494638
ISBN-10: 0471494631
Pagini: 464
Dimensiuni: 152 x 229 x 27 mm
Greutate: 0.74 kg
Ediția:2nd Revised edition
Editura: Wiley
Locul publicării:Chichester, United Kingdom

Public țintă

Like the successful hardback edition, this book will be useful to Senior Undergraduates and Postgraduates taking courses in optimization from mathematics, computers science and operations research. It will also be of interest to Scientists and Engineers using optimization techniques, Researchers and Consultants.

Descriere

Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers revised coverage of basic theory and standard techniques, with updated discussions of line search methods, Newton and quasi-Newton methods, and conjugate direction methods, as well as a comprehensive treatment of restricted step or trust region methods not commonly found in the literature. Also includes recent developments in hybrid methods for nonlinear least squares; an extended discussion of linear programming, with new methods for stable updating of LU factors; and a completely new section on network programming. Chapters include computer subroutines, worked examples, and study questions.