Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.

About the Author

ANTHONY V. FIACCO is Professor Emeritus of Operations Research and Applied Science at George Washington University, Washington, D.C. From 1960 to 1971, Dr. Fiacco was an Operations Analyst for the Research Analysis Corporation in McLean, Virginia, where he was Project Chairman of a study that pioneered several breakthroughs in nonlinear programming (NLP) methodology. He is the author or coauthor of numerous papers on NLP theory and applications, the coauthor with Garth P. McCormick in 1968 of a Lanchester prize-winning book on barrier and penalty function methodology, and the editor of several books, including Mathematical Programming with Data Perturbations I and II (both titles, Marcel Dekker, Inc.). A prominent contributor to the development of computable methods for sensitivity and stability analysis, Dr. Fiacco received the Ph.D. degree 1967 in applied mathematics from Northwestern University, Evanston, Illinois. Since 1979, he has organized, at the George Washington University, the only annual conference completely devoted to sensitivity and stability issues.

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