Applied Mathematical Programming
by S. Bradley, A. Hax, T. Magnanti
Publisher: Addison-Wesley 1977
Number of pages: 716
This book shows you how to model a wide array of problems, and explains the mathematical algorithms and techniques behind the modeling. Covered are topics such as linear programming, duality theory, sensitivity analysis, network/dynamic programming, integer programming, non-linear programming, and my favorite, large-scale problems modeling/solving, etc.
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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 Katta G. Murty - Springer
This is a Junior level book on some versatile optimization models for decision making in common use. The aim of this book is to develop skills in mathematical modeling, and in algorithms and computational methods to solve and analyze these models.
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 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.