Bi-level Strategies in Semi-infinite Programming

Pirmais vāks
Springer Science & Business Media, 2003. gada 31. aug. - 202 lappuses
Semi-infinite optimization is a vivid field of active research. Recently semi infinite optimization in a general form has attracted a lot of attention, not only because of its surprising structural aspects, but also due to the large number of applications which can be formulated as general semi-infinite programs. The aim of this book is to highlight structural aspects of general semi-infinite programming, to formulate optimality conditions which take this structure into account, and to give a conceptually new solution method. In fact, under certain assumptions general semi-infinite programs can be solved efficiently when their bi-Ievel structure is exploited appropriately. After a brief introduction with some historical background in Chapter 1 we be gin our presentation by a motivation for the appearance of standard and general semi-infinite optimization problems in applications. Chapter 2 lists a number of problems from engineering and economics which give rise to semi-infinite models, including (reverse) Chebyshev approximation, minimax problems, ro bust optimization, design centering, defect minimization problems for operator equations, and disjunctive programming.

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Saturs

INTRODUCTION
5
11 Standard semiinfinite programming
6
12 General semiinfinite programming
8
13 The misconception about the generality of GSIP
10
14 Development to a field of active research
12
EXAMPLES AND APPLICATIONS
15
21 Chebyshev and reverse Chebyshev approximation
16
22 Minimax problems
18
43 Dual first order optimality conditions
120
431 The standard semiinfinite case
122
432 The completely convex case
124
433 The convex case
127
434 The C² case with Reduction Ansatz
130
435 The C¹ case
132
44 Second order optimality conditions
146
BILEVEL METHODS FOR GSIP
149

23 Robust optimization
19
24 Design centering
22
26 Disjunctive programming
26
TOPOLOGICAL STRUCTURE OF THE FEASIBLE SET
29
311 A projection formula
31
312 A bilevel formula and semicontinuity properties
35
313 A setvalued mapping formula
45
314 The local structure of M
46
315 The completely convex case
48
32 Index set mappings with functional constraints
50
322 The linear case
51
323 The C¹ case
64
324 The C² case
66
325 Genericity results
70
OPTIMALITY CONDITIONS
89
42 First order approximations of the feasible set
94
421 General constraint qualifications
95
422 Descriptions of the linearization cones
100
423 Degenerate index sets
112
51 Reformulations of GSIP
150
512 The MPEC reformulation of GSIP
152
513 A regularization of MPEC by NCP functions
153
514 The regularized Stackelberg game
156
52 Convergence results for a bilevel method
158
521 A parametric reduction lemma
159
522 Convergence of global solutions
161
523 Convergence of Fritz John points
162
524 Quadratic convergence of the optimal values
166
525 An outer approximation property
167
53 Other bilevel approaches and generalizations
171
COMPUTATIONAL RESULTS
175
61 Design centering in two dimensions
176
62 Design centering in higher dimensions
181
63 Robust optimization
182
64 Optimal error bounds for an elliptic operator equation
185
FINAL REMARKS
191
References
195
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