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 Guido Schaefer - Utrecht University
From the table of contents: Preliminaries (Optimization Problems); Minimum Spanning Trees; Matroids; Shortest Paths; Maximum Flows; Minimum Cost Flows; Matchings; Integrality of Polyhedra; Complexity Theory; Approximation Algorithms.
by S. Bradley, A. Hax, T. Magnanti - Addison-Wesley
This book shows you how to model a wide array of problems. Covered are topics such as linear programming, duality theory, sensitivity analysis, network/dynamic programming, integer programming, non-linear programming, and my favorite, etc.
by U. Helmke, J. B. Moore - Springer
Aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control systems, signal processing, and linear algebra. The problems solved are those of linear algebra and linear systems theory.
by Thomas S. Ferguson - UCLA
From the table of contents: Stopping Rule Problems; Finite Horizon Problems; The Existence of Optimal Rules; Applications. Markov Models; Monotone Stopping Rule Problems; Maximizing the Rate of Return; Bandit Problems; Solutions to the Exercises.