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Multilevel Optimization: Algorithms and Applications

'Nonconvex Optimization and Its Applications'. Auflage 1998. Sprache: Englisch.
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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 goa... weiterlesen
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Multilevel Optimization: Algorithms and Applications als Buch
Produktdetails
Titel: Multilevel Optimization: Algorithms and Applications

ISBN: 0792346939
EAN: 9780792346937
'Nonconvex Optimization and Its Applications'.
Auflage 1998.
Sprache: Englisch.
Herausgegeben von A. Migdalas, Panos M. Pardalos, Peter Varbrand
SPRINGER VERLAG GMBH

31. Dezember 1997 - gebunden - 386 Seiten

Beschreibung

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).

Inhaltsverzeichnis

Preface.
1. Congested O-D Trip Demand Adjustment Problem: Bilevel Programming Formulation and Optimality Conditions; Yang Chen, M. Florian.
2. Determining Tax Credits for Converting Nonfood Crops to Biofuels: An Application of Bilevel Programming; J.F. Bard, et al.
3. Multilevel Optimization Methods in Mechanics; P.D. Panagiotopoulos, et al.
4. Optimal Structural Design in Nonsmooth Mechanics; G.E. Stavroulakis, H. Günzel.
5. Optimizing the Operations of an Aluminium Smelter Using Non-Linear Bi-Level Programming; M.G. Nicholls.
6. Complexity Issues in Bilevel Linear Programming; Xiaotie Deng.
7. The Computational Complexity of Multi-Level Bottleneck Programming Problems; T. Dudás, et al.
8. On the Linear Maxmin and Related Programming Problems; C. Audet, et al.
9. Piecewise Sequential Quadratic Programming for Mathematical Programs with Nonlinear Complementarity Constraints; Zhi-Quan Luo, et al.
10. A New Branch and Bound Method for Bilevel Linear Programs; Hoang Tuy, S. Ghannadan.
11. A Penalty Method for Linear Bilevel Programming Problems; M.A. Amouzegar, K. Moshirvaziri.
12. An Implicit Function Approach to Bilevel Programming Problems; S. Dempe.
13. Bilevel Linear Programming, Multiobjective Programming, and Monotonic Reverse Convex Programming; Hoang Tuy.
14. Existence of Solutions to Generalized Bilevel Programming Problem; M.B. Lignola, J. Morgan.
15. Application of Topological Degree Theory to Complementarity Problems; V.A. Bulavsky, et al.
16. Optimality and Dualityin Parametric Convex Lexicographic Programming; C.A. Floudas, S. Zlobec. Index.

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