Lectures on Optimization: Theory and Algorithms
by John Cea
Publisher: Tata Institute of Fundamental Research 1978
Number of pages: 237
Contents: Differential Calculus in Normed Linear Spaces; Minimization of Functionals - Theory; Minimization Without Constraints - Algorithms; Minimization with Constraints - Algorithms; Duality and Its Applications; Elements of the Theory of Control and Elements of Optimal Design.
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by P.-A. Absil, R. Mahony, R. Sepulchre - Princeton University Press
Many science and engineering problems can be rephrased as optimization problems on matrix search spaces endowed with a manifold structure. This book shows how to exploit the structure of such problems to develop efficient numerical algorithms.
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The aim of this paper is to help practitioners to understand robust optimization and to successfully apply it in practice. We provide a brief introduction to robust optimization, and also describe important do's and don'ts for using it in practice.
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These are notes for an introductory course in linear programming. The four basic components of the course are modeling, solution methodology, duality theory, and sensitivity analysis. We focus on the simplex algorithm due to George Dantzig.