Critical multipliers in variational systems via second-order generalized differentiation.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 605, doi. 10.1007/s10107-017-1155-2
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- Publication type:
- Article
Works matching IS 00255610 AND DT 2018 AND VI 169 AND IP 2
Results: 10
1
2
Bilevel programming for generating discrete representations in multiobjective optimization.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 585, doi. 10.1007/s10107-017-1149-0
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- Publication type:
- Article
3
Mixed integer reformulations of integer programs and the affine TU-dimension of a matrix.
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- Mathematical Programming, 2018, v. 169, n. 2, p. 565, doi. 10.1007/s10107-017-1147-2
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- Article
4
SOCP reformulation for the generalized trust region subproblem via a canonical form of two symmetric matrices.
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- Mathematical Programming, 2018, v. 169, n. 2, p. 531, doi. 10.1007/s10107-017-1145-4
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- Publication type:
- Article
5
Distributionally robust optimization with matrix moment constraints: Lagrange duality and cutting plane methods.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 489, doi. 10.1007/s10107-017-1143-6
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- Publication type:
- Article
6
Piecewise static policies for two-stage adjustable robust linear optimization.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 649, doi. 10.1007/s10107-017-1142-7
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- Publication type:
- Article
7
Stochastic optimization using a trust-region method and random models.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 447, doi. 10.1007/s10107-017-1141-8
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- Publication type:
- Article
8
Matroid optimisation problems with nested non-linear monomials in the objective function.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 417, doi. 10.1007/s10107-017-1140-9
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- Publication type:
- Article
9
Deriving convex hulls through lifting and projection.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 377, doi. 10.1007/s10107-017-1138-3
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- Publication type:
- Article
10
Global convergence rate analysis of unconstrained optimization methods based on probabilistic models.
- Published in:
- Mathematical Programming, 2018, v. 169, n. 2, p. 337, doi. 10.1007/s10107-017-1137-4
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- Publication type:
- Article