Constrained Optimization and Image Space Analysis
Volume 1: Separation of Sets and Optimality Conditions
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Beschreibung
Over the last twenty years, Professor Franco Giannessi, a highly respected researcher, has been working on an approach to optimization theory based on image space analysis. His theory has been elaborated by many other researchers in a wealth of papers. Constrained Optimization and Image Space Analysis unites his results and presents optimization theory and variational inequalities in their light.
It presents a new approach to the theory of constrained extremum problems, including Mathematical Programming, Calculus of Variations and Optimal Control Problems. Such an approach unifies the several branches: Optimality Conditions, Duality, Penalizations, Vector Problems, Variational Inequalities and Complementarity Problems. The applications benefit from a unified theory.
A peerless monograph, presenting a new approach to the theory of constrained extremum problems, including Mathematical Programming, Calculus of Variations and Optimal Control Problems Applications are seen for the first time in the light of a unified theory An excellent reference for researchers in Analysis, Applied Mathematics, Mathematical Physics and many other applied branches
Autor*in
Franco Giannessi
Themen in »Constrained Optimization and Image Space Analysis«
Convexity calculus design mechanics optimization optimization, image space analysis, applications of mathemat programming combinatorics
Stimmen zu »Constrained Optimization and Image Space Analysis«
From the reviews:
"This is a very substantial and useful monograph … . it would be an excellent reference in a course at the graduate level in engineering or the advanced undergraduate level in mathematics, as well as for working mathematicians interested in optimization. This book is of unusually fine quality … it will amply repay the time required. A notable feature of this work is the depth and completeness of coverage of many of the topics. … Another aspect … is the extensive use of examples." (Stephen M. Robinson, SIAM Review, Vol. 48 (2), 2006)
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