Linear Optimisation and Numerical Analysis
by Ian Craw
Publisher: University of Aberdeen 2002
Number of pages: 151
The overall aim of the course is: to describe the simplex algorithm and show how it can be used to solve real problems; to show how previous results in linear algebra give a framework for understanding the simplex algorithm; and to place the simplex algorithm in a more general context by describing other calculus-based and computer based optimization algorithms.
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by Kurt Mehlhorn, Chee Yap - New York University
Contents: Introduction to Geometric Nonrobustness; Modes of Numerical Computation; Geometric Computation; Arithmetic Approaches; Geometric Approaches; Exact Geometric Computation; Perturbation; Filters; Algebraic Background; Zero Bounds; etc.
by Svein Linge, Hans Petter Langtangen - Springer
This book presents Python programming as a key method for solving mathematical problems. The style is accessible and concise, the emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.
by George W. Collins, II - NASA ADS
'Fundamental Numerical Methods and Data Analysis' can serve as the basis for a wide range of courses that discuss numerical methods used in science. The author provides examples of the more difficult algorithms integrated into the text.
by Autar K Kaw, Egwu Eric Kalu - Lulu.com
The textbook is written for engineering undergraduates taking a course in numerical methods. It offers a treatise to numerical methods based on a holistic approach and short chapters. The authors included examples of real-life applications.