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 Marius Durea, Radu Strugariu - De Gruyter Open
Starting with the case of differentiable data and the classical results on constrained optimization problems, continuing with the topic of nonsmooth objects involved in optimization, the book concentrates on both theoretical and practical aspects.
by C.T. Kelley - Society for Industrial Mathematics
This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis.
by Sebastien Bubeck - arXiv.org
This text presents the main complexity theorems in convex optimization and their algorithms. Starting from the fundamental theory of black-box optimization, the material progresses towards recent advances in structural and stochastic optimization.
by Jim Burke - University of Washington
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.