We focus on the handling of overlapping solutions in evolutionary multiobjective optimization (EMO) algorithms. First we show that there exist a large number of overlapping soluti...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
We review the concepts of hypertree decomposition and hypertree width from a graph theoretical perspective and report on a number of recent results related to these concepts. We al...
Georg Gottlob, Martin Grohe, Nysret Musliu, Marko ...
We develop algorithms for finding minimum energy disjoint paths in an all-wireless network, for both the node and linkdisjoint cases. Our major results include a novel polynomial...
We present the first constant-factor approximation algorithm for network design with multiple commodities and economies of scale. We consider the rent-or-buy problem, a type of m...