The predominant measure for the performance of an algorithm is its worst-case
approximation guarantee. While worst-case approximations give desirable robustness …

We study a new optimization problem called submodular maximization under submodular
cover (SMSC), which requires to find a fixed-size set such that one monotone submodular …

Search and tracking is the problem of locating a moving target and following it to its
destination. In this work, we consider a scenario in which the target moves across a large …

Many relevant applications from diverse areas such as marketing, wildlife conservation, and
defending critical infrastructure can be modeled as interdiction games. In this work, we …

In this paper we design a new primal-dual algorithm for the classic discrete optimization
problem of maximizing a monotone submodular function subject to a cardinality constraint …

Submodular function maximization is an attractive optimization model and also a well-
studied problem with a variety of algorithms available. Constraint generation (CG) …

Although submodular maximization generalizes many fundamental problems in discrete
optimization, lots of real-world problems are non-submodular. In this paper, we consider the …

Submodular optimization has been well studied in combinatorial optimization. However,
there are few works considering about non-submodular optimization problems which also …

Algorithm Engineering for Generic Subset Optimization Problems Page 1 Algorithm
Engineering for Generic Subset Optimization Problems Masterarbeit zur Erlangung des …

The submodular function maximization is an attractive optimization model that appears in
many real applications. Although a variety of greedy algorithms quickly find good feasible …