Results 261 to 270 of about 16,647 (299)
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Semi-Infinite Programming and Applications to Minimax Problems
Annals of Operations Research, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stanislav Zakovic, Berç Rustem
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On Exchange Methods for Nonlinear Semi-Infinite Programs
Asia-Pacific Journal of Operational Research, 2021A new exchange method is presented for semi-infinite optimization problems with polyhedron constraints. The basic idea is to use an active set strategy as exchange rule to construct an approximate problem with finitely many constraints at each iteration.
Liping Zhang 0008, Shouqiang Du
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ACM Transactions on Mathematical Software, 2004
SIPAMPL is an environment for coding semi-infinite programming (SIP) problems. This environment includes a database containing a set of SIP problems that have been collected from the literature and a set of routines. It allows users to code their own SIP problems in AMPL, to use any problem already in the database, and to develop and test any SIP ...
A. Ismael F. Vaz +2 more
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SIPAMPL is an environment for coding semi-infinite programming (SIP) problems. This environment includes a database containing a set of SIP problems that have been collected from the literature and a set of routines. It allows users to code their own SIP problems in AMPL, to use any problem already in the database, and to develop and test any SIP ...
A. Ismael F. Vaz +2 more
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On Nesterov's Approach to Semi-infinite Programming
Acta Applicandae Mathematica, 2002The author generalizes the Nesterov's construction for the reduction of various classes of optimization problems to the semidefinite programming form. The author shows that all Nesterov's results can be generalized to `cones of squares' generated by arbitrary bilinear maps between finite-dimensional vector spaces.
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Randomized Algorithms for Semi-Infinite Programming Problems
2003 European Control Conference (ECC), 2003In this paper, we explore the possibility of applying Monte Carlo methods (i.e., randomization) to semi-infinite programming problems. Equivalent stochastic optimization problems are derived for a general class of semi-infinite programming problems. For the equivalent stochastic optimization problems, algorithms based on stochastic approximation and ...
V B Tadic, S P Meyn, R Tempo
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Perfect duality in semi–infinite and semidefinite programming
Mathematical Programming, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kenneth O. Kortanek, Qinghong Zhang
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2010
Semi-infinite programs are constrained optimization problems in which the number of decision variables is finite, but the number of constraints is infinite. In this chapter, we treat a class semi-infinite programming problems in which the constraints are indexed by a compact set.
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Semi-infinite programs are constrained optimization problems in which the number of decision variables is finite, but the number of constraints is infinite. In this chapter, we treat a class semi-infinite programming problems in which the constraints are indexed by a compact set.
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Discretization in semi-infinite programming: the rate of convergence
Mathematical Programming, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Subdifferentials of Marginal Functions in Semi-infinite Programming
SIAM Journal on Optimization, 2010This paper proposes two new constraint qualification conditions (CQs) which are useful for a unified study of CQs from both a convex analysis and a nonsmooth analysis point of view. Our CQs cover the existing CQs of Mangasarian-Fromovitz and Farkas-Minkowski types. Some sufficient conditions for the validity of the new CQs are given.
Thai Doan Chuong +2 more
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Semi-infinite quadratic programming
Operations-Research-Spektrum, 1979A method is presented for minimizing a definite quadratic function under an infinite number of linear inequality restrictions. Special features of the method are that it generates a sequence of feasible solutions and a sequence of basic solutions simultaneously and that it has very favourable properties concerning numerical stability.
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