In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...
In this paper, we examine how adding objectives to a given optimization problem affects the computation effort required to generate the set of Pareto-optimal solutions. Experime...
Dimo Brockhoff, Tobias Friedrich, Nils Hebbinghaus...
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
Of interest here are linear data fitting problems with uncertain data which lie in a given uncertainty set. A robust counterpart of such a problem may be interpreted as the probl...
This paper considers the minimax filtering problem in which the supremum norm of weighted error sequence is minimized. It is shown that the minimax solution is also the optimal Se...