Results 221 to 230 of about 1,898 (263)

On Exchange Methods for Nonlinear Semi-Infinite Programs

Asia-Pacific Journal of Operational Research, 2021
A 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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On Nesterov's Approach to Semi-infinite Programming

Acta Applicandae Mathematica, 2002
The 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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SIPAMPL

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, Edite M. G. P. Fernandes, M. Paula S. F. Gomes   +2 more
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A Smoothing Newton Method for Semi-Infinite Programming

Journal of Global Optimization, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dong-Hui Li, Liqun Qi 0001, Judy Tam, Soon-Yi Wu   +3 more
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Semi-infinite Programming

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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Randomized Algorithms for Semi-Infinite Programming Problems

2003 European Control Conference (ECC), 2003
In 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, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kenneth O. Kortanek, Qinghong Zhang
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On generalized semi-infinite programming

Top, 2006
This paper surveys some basic properties of the class of generalized semi-infinite programming problems (GSIP) where the infinite index set of inequality constraints depends on the state variables and all emerging functions are assumed to be continuously differentiable. There exists a wide range of applications which can be modelled as a (GSIP).
Jan -J. Rückmann, Juan Alfredo Gómez
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Discretization in semi-infinite programming: the rate of convergence

Mathematical Programming, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Feasible Method for Generalized Semi-Infinite Programming

Journal of Optimization Theory and Applications, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stein, O., Winterfeld, A.
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