Maximum-Profit Domination with Matroid Constraints: A Fixed-Parameter Algorithm and Applications? René van Bevern1,2 1 Novosibirsk State University, Novosibirsk, Russian Federation, rvb@nsu.ru 2 Sobolev Institute of Mathematics of SB RAS, Novosibirsk, Russian Federation Keywords: social network analysis, routing, facility location, matroid optimiza- tion, parameterized complexity, NP-hard problem. This lecture presents ongoing joint work with Oxana Yu. Tsidulko (Novosibirsk) and Philipp Zschoche (Berlin) on fixed-parameter algorithms for the following generalization of Set Cover and Dominating Set. It models various social network analysis, routing, and facility location problems: Problem (Max-Profit Domination with Matroid Constraint (MDMC)). Input: A universe U , for each u, v ∈ U a profit puv ∈ N ∪ {0} from dominating u by v, a cost cv ∈ N ∪ {0, ∞} for using v as dominator, and a matroid (U, I). Output: Two disjoint sets D ] C ⊆ U such that D ∈ I and that maximize X X max puv − cv . v∈D u∈C v∈D Informally, we find sets C, D ⊆ U so as to maximize the profit from dominating the elements in C by elements in D minus the cost for the dominators in D. Example. We obtain the classical problem of covering a maximum number of elements of an universe V using at most k sets of a collection C ⊆ 2V by choosing U = V ∪ C, I = {C 0 ⊆ C : |C 0 | ≤ k}, and, for each u, v ∈ U , ( ( 0 if v ∈ C, 1 if v ∈ C such that u ∈ v, cv = puv = ∞ if v ∈ V , 0 otherwise. We prove the following theorem and present applications to social network analysis, routing, and facility location problems. Theorem. A maximum-profit solution to MDMC with |C| = k is computable in 2O(k) · poly(n) time, i. e. in poly-time for k ∈ O(log n), where n is the input size. Herein, the universe U , costs cv and profits puv for each u, v ∈ U are given explicitly in the input, whereas the matroid (U, I) is given as an oracle that, in constant time, answers whether a subset of U belongs to I. ? This research is supported by the Russian Foundation for Basic Research under grants 16-31-60007 mol a dk (René van Bevern) and 18-31-00470 mol a (Oxana Yu. Tsidulko), and by the Ministry of Science and Education of the Russian Federation under the 5-100 excellence programme.