Optimizers for Sub-Sums subject to a Sum- and a Schur-Convex Constraint with Applications to Estimation of Eigenvalues

@article{Kovaec2003OptimizersFS,
  title={Optimizers for Sub-Sums subject to a Sum- and a Schur-Convex Constraint with Applications to Estimation of Eigenvalues},
  author={A. Kova{\vc}ec and J. Merikoski and O. Pikhurko and A. Virtanen},
  journal={Mathematical Inequalities & Applications},
  year={2003},
  pages={745-763}
}
A complete solution is presented for the problem of determining the sets of points at which the functions (x1, . . . , xn) → xk + . . . + xl, subject to the constraints M x1 . . . xn m, x1 + x2 + . . . + xn = a, and g(x1) + g(x2) + . . . + g(xn) = b, with g strictly convex continuous, assume their maxima and minima. Applications are given. Mathematics subject classification (2000): 90C25, 26D15, 15A42. 
2 Citations
Majorization and k-majorization as an approach to some problems in optimization and eigenvalue estimation
Convex separable minimization problems with a linear constraint and bounded variables
  • S. Stefanov
  • Mathematics, Computer Science
  • Int. J. Math. Math. Sci.
  • 2005
  • 16
  • PDF

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