by Jim Burke
Publisher: University of Washington 2012
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 since it offers a complete framework for discussing both the geometry and duality theory for linear programs.
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by Ozgur Baskan (ed.) - InTech
This book covers state-of-the-art optimization methods and their applications in wide range especially for researchers and practitioners who wish to improve their knowledge in this field. It covers applications in engineering and various other areas.
by Bruce A. McCarl, Thomas H. Spreen - Texas A&M University
This book is intended to both serve as a reference guide and a text for a course on Applied Mathematical Programming. The text concentrates upon conceptual issues, problem formulation, computerized problem solution, and results interpretation.
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.
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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.