Results 211 to 220 of about 2,908,938 (258)

Vector equilibrium problem and vector optimization

European Journal of Operational Research, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
C. J. Goh, X. Q. Yang
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Vector Ordinal Optimization

Journal of Optimization Theory and Applications, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Q. C., Ho, Y. C., Jia, Q. S.
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Optimality Conditions for Vector Optimization Problems

Journal of Optimization Theory and Applications, 2009
The paper considers vector optimization problems (VOP) of the form \[ \min F(x) \text{ subject to } u_i(x) \leq 0, i\in\{1, \dots, m\}; v_j(x) =0, j\in\{1, \dots, n\}, \] where \(F:X \rightarrow \mathbb{R}^L\) and \(u_i, v_j: X\rightarrow \mathbb{R}\) and \(X\) is a Banach space.
N. J. Huang, J. Li, S. Y. Wu
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Vector Variational Inequality and Vector Pseudolinear Optimization

Journal of Optimization Theory and Applications, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaoqi Yang
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Vector optimization vs. vectorization

Journal of Parallel and Distributed Computing, 1988
This paper differentiates between vectorization (and also concurrentization) and vector optimization (or concurrency optimization). Vectorization (concurrentization) is the process of translating serial DO (or FOR) loops into vector code for a vector computer (concurrent code for a multiprocessor computer). Vector optimization (concurrency optimization)
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Some Optimality Conditions in Vector Optimization

Journal of Information and Optimization Sciences, 1989
Abstract In this paper, by means of a theorem of the alternative for generalized systems, weak alternative is introduced and some necessary and/or sufficient optimality conditions such as a generalized saddle-point condition is deduced; a simple proof of the Fritz John conditions for multiobjective functions is given.
CAMBINI A., MARTEIN, LAURA
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An Optimal Set of Discriminant Vectors

IEEE Transactions on Computers, 1975
A new method for the extraction of features in a two-class pattern recognition problem is derived. The main advantage is that the method for selecting features is based entirely upon discrimination or separability as opposed to the more common approach of fitting.
Donald H. Foley, John W. Sammon Jr.
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