Applied Mathematical Programming Using Algebraic Systems
by Bruce A. McCarl, Thomas H. Spreen
Publisher: Texas A&M University 2011
Number of pages: 567
This book is intended to both serve as a reference guide and a text for a course on Applied Mathematical Programming. The material presented will concentrate upon conceptual issues, problem formulation, computerized problem solution, and results interpretation. Solution algorithms will be treated only to the extent necessary to interpret solutions and overview events that may occur during the solution process.
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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 D. P. Williamson, D. B. Shmoys - Cambridge University Press
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. It is organized around techniques for designing approximation algorithms, including greedy and local search algorithms.
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.
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The aim of this paper is to help practitioners to understand robust optimization and to successfully apply it in practice. We provide a brief introduction to robust optimization, and also describe important do's and don'ts for using it in practice.