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Covering the current state of the art, this book explores an important and central issue in convex optimization: optimality conditions. Although many results presented in the chapters can also be proved in infinite dimensions, the text focuses on finite dimensions to allow for much deeper results and a better understanding of the structures involved in a convex optimization problem. The authors include examples wherever needed, details of major results, and proofs of the main results.

Produktbeschreibung
Covering the current state of the art, this book explores an important and central issue in convex optimization: optimality conditions. Although many results presented in the chapters can also be proved in infinite dimensions, the text focuses on finite dimensions to allow for much deeper results and a better understanding of the structures involved in a convex optimization problem. The authors include examples wherever needed, details of major results, and proofs of the main results.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Anulekha Dhara earned her Ph.d. in IIT Delhi and subsequently moved to IIT Kanpur for her post-doctoral studies. Currently, she is a post-doctoral fellow in Mathematics at the University of Avignon, France. Her main area of interest is optimization theory.

Joydeep Dutta is an Associate Professor of Mathematics at the Indian Institute of Technology, (IIT) Kanpur. His main area of interest is optimization theory and applications.