Abstract Machine scheduling problems are a long-time key domain of algorithms and
complexity research. A novel approach to machine scheduling problems are fixed …

We study several classical decision problems on finite automata under the (Strong)
Exponential Time Hypothesis. We focus on three types of problems: universality …

The knapsack problem (KP) is a very famous NP-hard problem in combinatorial
optimization. Also its generalization to multiple dimensions named d-dimensional knapsack …

Abstract In the Weighted Treewidth-η Deletion problem we are given a node-weighted graph
G and we look for a vertex subset X of minimum weight such that the treewidth of G—X is at …

Cycle packing is a fundamental problem in optimization, graph theory, and algorithms.
Motivated by recent advancements in finding vertex-disjoint paths between a specified set of …

We obtain new polynomial kernels and compression algorithms for Path Cover and Cycle
Cover, the well-known generalizations of the classical Hamiltonian Path and Hamiltonian …

Abstract In the Generalized Noah's Ark Problem, one is given a phylogenetic tree on a set of
species X and a set of projects for each species. Each project comes with a cost and raises …

Abstract The 1| s-batch (∞), rj|∑ wj U j scheduling problem takes as input a batch setup time
Δ and a set of n jobs, each having a processing time, a release date, a weight, and a due …

We study pattern matching problems on two major representations of uncertain sequences
used in molecular biology: weighted sequences (also known as position weight matrices …

A Bayesian network is a directed acyclic graph that represents statistical dependencies
between variables of a joint probability distribution. A fundamental task in data science is to …