Foundations of Mathematical Optimization: Convex Analysis without Linearity
mar 2013 · Mathematics and Its Applications Libro 388 · Springer Science & Business Media
Ebook
585
pagine
reportValutazioni e recensioni non sono verificate Scopri di più
Informazioni su questo ebook
Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization.
Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.
Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.
Valuta questo ebook
Dicci cosa ne pensi.
Informazioni sulla lettura
Smartphone e tablet
Installa l'app Google Play Libri per Android e iPad/iPhone. L'app verrà sincronizzata automaticamente con il tuo account e potrai leggere libri online oppure offline ovunque tu sia.
Laptop e computer
Puoi ascoltare gli audiolibri acquistati su Google Play usando il browser web del tuo computer.
eReader e altri dispositivi
Per leggere su dispositivi e-ink come Kobo e eReader, dovrai scaricare un file e trasferirlo sul dispositivo. Segui le istruzioni dettagliate del Centro assistenza per trasferire i file sugli eReader supportati.
