by Stephen Boyd, Lieven Vandenberghe
Publisher: Cambridge University Press 2004
Number of pages: 730
Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
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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 Alexander Bolonkin - viXra.org
This book describes new method of optimization (''Method of Deformation of Functional'') that has the advantages at greater generality and flexibility as well as the ability to solve complex problems which other methods cannot solve.
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.
by Katta G. Murty
This book provides an in-depth and clear treatment of all the important practical, technical, computational, geometric, and mathematical aspects of the Linear Complementarity Problem, Quadratic Programming, and their various applications.