Multilevel Optimization: Algorithms and Applications

A. Migdalas

ISBN 10: 0792346939 / ISBN 13: 9780792346937

Published by Springer Us Dez 1997, 1997

About this Item

Neuware - 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).

Seller Inventory # 9780792346937

Bibliographic Details

• Title: Multilevel Optimization: Algorithms and Applications
• Publisher: Springer Us Dez 1997
• Publication Date: 1997
• Language: English
• ISBN 10: 0792346939
• ISBN 13: 9780792346937
• Binding: Buch
• Condition: Neu
• Dimensions: 242W x 160H x 28D millimeters 242 millimeters width by 160 millimeters height by 28 millimeters depth
• Weight: 744 grams

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).