by A. Ben-Tal, L. El Ghaoui, A. Nemirovski
Publisher: Princeton University Press 2009
Number of pages: 564
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject.
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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 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 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 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.