Multilevel Optimization: Algorithms and Applications (Nonconvex Optimization and Its Applications (Closed))

Migdalas, A. (Editor) / Pardalos, Panos M. (Editor) / Värbrand, Peter (Editor)

ISBN 10: 146137989X / ISBN 13: 9781461379898

Published by Springer, 2012

About this Item

reprint edition. 412 pages. 9.45x6.30x0.93 inches. In Stock.

Seller Inventory # x-146137989X

Bibliographic Details

• Title: Multilevel Optimization: Algorithms and Applications (Nonconvex Optimization and Its Applications (Closed))
• Publisher: Springer
• Publication Date: 2012
• Language: English
• ISBN 10: 146137989X
• ISBN 13: 9781461379898
• Binding: Paperback
• Condition: Brand New

About this title

Synopsis

Researchers working with nonlinear programming often claim "the word is non­ linear" indicating that real applications require nonlinear modeling. The same is true for other areas such as multi-objective programming (there are always several goals in a real application), stochastic programming (all data is uncer­ tain and therefore stochastic models should be used), and so forth. In this spirit we claim: The word is multilevel. In many decision processes there is a hierarchy of decision makers, and decisions are made at different levels in this hierarchy. One way to handle such hierar­ chies is to focus on one level and include other levels' behaviors as assumptions. Multilevel programming is the research area that focuses on the whole hierar­ chy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of opti­ mization problems which must be solved in a predetermined sequence. If only two levels are considered, we have one leader (associated with the upper level) and one follower (associated with the lower level).