Semi-Infinite Programming: Recent Advances

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Miguel Ángel Goberna, Marco A. López
Springer Science & Business Media, 2013. gada 11. nov. - 386 lappuses
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Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite. This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different scientific and technological fields.
The volume is divided into four parts. Part I reviews the first decade of SIP (1962-1972). Part II analyses convex and generalised SIP, conic linear programming, and disjunctive programming. New numerical methods for linear, convex, and continuously differentiable SIP problems are proposed in Part III. Finally, Part IV provides an overview of the applications of SIP to probability, statistics, experimental design, robotics, optimization under uncertainty, production games, and separation problems.
Audience: This book is an indispensable reference and source for advanced students and researchers in applied mathematics and engineering.

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Saturs

ABOUT DISJUNCTIVE OPTIMIZATION
45
ON REGULARITY AND OPTIMALITY IN NONLINEAR
59
ASYMPTOTIC CONSTRAINT QUALIFICATIONS AND
75
STABILITY OF THE FEASIBLE SET MAPPING IN CON
101
ON CONVEXLOWER LEVEL PROBLEMSINGENERAL
121
ON DUALITY THEORY OF CONIC LINEAR PROBLEMS
135
Conic linear problems
136
Problem of moments
145
R eferences
194
FIRSTORDER ALGORITHMS FOR OPTIMIZATION 197
196
SemiInfinite MinMax Problems
199
Rate of Convergence of Algorithm 2 2
206
Minimization of the Maximum Eigenvalue of a Symmetric Matrix
207
Problems with SemiInfinite Constraints
211
Problems with Maximum Eigenvalue Constraints
216
A Numerical Example
217

Semiinfinite programming
152
Continuous linear programming
155
References
164
NUMERICAL METHODS
166
TWO LOGARITHMIC BARRIER METHODS FOR CON
169
A bundle method using esubgradients
170
Description of the barrier method
172
Properties of the method
175
Numerical aspects
181
Numerical example
182
A regularized logbarrier method
185
Numerical results of the regularized method
191
Conclusions
193
Conclusion
219
METHOD FOR LINEAR SEMIINFINITE PROGRAM
221
11
235
References
246
4
252
References
269
ON STABILITY OF GUARANTEED ESTIMATION 299
298
255
325
OPTIMIZATION UNDER UNCERTAINTY AND LINEAR
327
Conclusions
340
SEMIINFINITE ASSIGNMENT ANDTRANSPORTATION
349
THE OWEN SET AND THE CORE OF SEMIINFINITE
365
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