An Introduction to Unconstrained Optimisation
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.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Searching for an optimum
Direct search methods
Gradient methods I
Gradient methods II
Optimisation in practice
arbitrary starting point BBC Basic bracketing interval Chapter components computed condition consider containing the minimum contour map contour plot convergence coordinate corresponds cubic search cycle defined determine the position direct search methods discussed display DSC algorithm E(dit efficient eigenvalues estimate Example Let Exercise F(xm F(xn Fibonacci search find the minimum function evaluations function F Gauss-Newton algorithm Gauss-Newton method global minimum global optimum golden section search gradient vector grid hessian matrix illustrates internal point iterations line searches local minimum locate maximum error menu minima minimisation minimum of F modified n-dimensional Newton's method number of function numerical optimisation obtained optimisation method orthogonal positive definite quadratic approximation quadratic function quadratic search Quasi-Newton Quasi-Newton methods saddle point satisfy screen search direction second derivatives Select some arbitrary sequence solution stationary points steepest descent algorithm step Stop sum of squares tion value of F variables zero
Page v - Site licenses are available for multiple use of software at £145.00 (inc VAT). Packs include master disc for copying, back-up disc and two books. To receive your software complete this form and return with your remittance to: Adam Hilger, IOP Publishing Ltd, Techno House, Redcliffe Way, Bristol BS1 6NX, England...
Page viii - Fourier Series and Transforms RD Harding A Simple Introduction to Numerical Analysis RD Harding and DA Quinney A Simple Introduction to Numerical Analysis Volume 2: Interpolation and Approximation RD Harding and DA Quinney From Number Theory to Secret Codes T Jackson Electric Circuit Theory BE Riches Introduction to Probability DR Robinson and AW Bowman A Computer Illustrated Text An Introduction to the Digital Analysis of Stationary Signals IP Castro Department of Mechanical Engineering, University...