Nonlinear Programming

by Olvi L. Mangasarian

This reprint of the 1969 book of the same name is a concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, structural design, and airline scheduling can be reduced to a constrained optimization problem. This book provides readers with the fundamentals needed to study and solve such problems.

Beginning with a chapter on linear inequalities and theorems of the alternative, basics of convex sets and separation theorems are then derived based on these theorems. This is followed by a chapter on convex functions that includes theorems of the alternative for such functions. These results are used in obtaining the saddlepoint optimality conditions of nonlinear programming without differentiability assumptions.

220 pages, Paperback

First published January 1, 1969

About the author

Olvi Leon Mangasarian (born 12 January 1934) is the John von Neumann Professor Emeritus of Mathematics and Computer Sciences in Department of Mathematics, University of California, San Diego and a recognised expert on optimization, data mining, and classification. In 2000, while professor in the Computer Science Department of the University of Wisconsin–Madison, he was awarded the Frederick W. Lanchester Prize for pioneering work in introducing the use of Operations Research techniques to the field of data mining with a particularly notable application being to breast cancer diagnosis.

Reviews

[Lucky1985mtp]

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