An introduction to unconstrained optimisation / J.J. McKeown, D. Meegan, and D. Sprevak.
By: McKeown, J. J.
Contributor(s): Meegan, D | Sprevak, D.Material type: BookSeries: A Computer illustrated text. Publisher: Bristol, England ; New York : Cambridge, England : A. Hilger ; ESM, c1990Description: x, 122 p. : ill. ; 21 cm.ISBN: 9780750300254; 0750300256 :; 0750300264 (IBM disc) :; 0750300272 (BBC 40/80 track disc) :; 0750300280 (text and disc) :; 0750300299 (network pack) :.Subject(s): Mathematical optimization | Numerical analysisDDC classification: 519.3 Online resources: Publisher description
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Integrating computer graphics and computer-based exercises with the text, An Introduction to Unconstrained Optimisation illustrates key methods with many examples and exercises using the computer. The book takes an elementary approach to this advanced topic, allowing readers to concentrate on learning and understanding the concepts of numerical optimization without unnecessary involvement in the intricacies of the subject. In addition, the modular approach of the software provides the opportunity to explore the algorithms used and to develop them further or try alternative approaches. Most of the algorithms are based upon a "hill-climbing" concept which, in two dimensions, is illustrated dynamically on the computer screen in the form of contour plots and search directions. The text is not specific to any particular microcomputer. Software is available for the BBC series of machines (40/80 track disc formats) and PC-compatible machines. The software is not available from your local bookstore, but is easily obtainable using the order form in the book. Keeping proofs and lists of methods to a minimum, the book is at a level suitable for a first course in numerical analysis, with a basic knowledge of calculus and vector algebra assumed. This book/software package will be of interest to professionals, teachers, and undergraduate students in mathematics, operational research, science, and engineering as well as economics and management courses that deal with quantitative methods
Getting started Searching for an optimum Line searches Direct search methods Steepest descent Conjugate gradients Newton's method Quasi-Newton methods Least squares Global optimization Optimisation in practice Bibliography Index
Includes bibliographical references (p. 119-120) and index.