Advances in Sensitivity Analysis and Parametric Programming

by Tomas Gal (Editor), H.J. Greenberg (Editor)

Overview

The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, shastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to define OR/MS are usually presented in terms of one subfield or the other. This separation comes about somewhat artificially: academic courses are conveniently subdivided with respect to prerequisites; an initial overview of OR/MS can be presented without requiring knowledge of probability and statistics; text books are conveniently divided into two related semester courses, with deterministic models coming first; academics tend to specialize in one subfield or the other; and practitioners also tend to be expert in a single subfield. But, no matter who is involved in an OR/MS modeling situation (deterministic or probabilistic - academic or practitioner), it is clear that a proper and correct treatment of any problem situation is accomplished only when the analysis cuts across this dichotomy.

Product Details

ISBN-13:	9780792399179
Publisher:	Springer US
Publication date:	05/31/1997
Series:	International Series in Operations Research & Management Science , #6
Edition description:	1997
Pages:	581
Product dimensions:	6.10(w) x 9.25(h) x 0.05(d)

Table of Contents

1. A Historical Sketch on Sensitivity Analysis and Parametric Programming.- 2. A Systems Perspective: Entity Set Graphs.- 3. Linear Programming 1: Basic Principles.- 4. Linear Programming 2: Degeneracy Graphs.- 5. Linear Programming 3: The Tolerance Approach.- 6. The Optimal Set and Optimal Partition Approach.- 7. Network Models.- 8. Qualitative Sensitivity Analysis.- 9. Integer and Mixed-Integer Programming.- 10. Nonlinear Programming.- 11. Multi-Criteria and Goal Programming.- 12. Shastic Programming and Robust Optimization.- 13. Redundancy.- 14. Feasibility and Viability.- 15. Fuzzy Mathematical Programming.

Editorial Reviews

Reports recent developments in the field made possible by interior point methods for linear programming. Includes a concise history, a general systems view, modern perspectives on traditional approaches in linear programming, recent results using the optimal partition approaches stemming from interior methods for both linear and quadratic programming, the special case of network models and how they lend themselves to special solution analysis, and qualitative sensitivity analysis. Also describes developments in related fields, such as mixed integer programming, non-linear programming using modeling languages, multi-criteria mathematical programming, stochastic programming and its application to financial models, redundancy in quadratic programs, diagnosing infeasibility in linear and nonlinear programs, and sensitivity analysis for fuzzy mathematical programming. Annotation c. by Book News, Inc., Portland, Or.

Booknews

‘... well-organized book can be highly recommended to all who are engaged in operations research and decision making with incomplete information and/or multiple criteria. I do not hesitate to congratulate the two editors on their excellent work.'
OR Spektrum, 22 (2000)

From the Publisher