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20162026
most citedMinimizing the Number of Tardy Jobs and Maximal Tardiness on a Single Machine is NP-hard

2 citations · 9 across the 18 of their papers we have counts for

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11 papers · 1 filter

cs.DS2026

Approximate Total Weighted Completion Time with Convex Controllable Processing Times

Klaus Heeger, Danny Hermelin, Dvir Shabtay

We study the single-machine scheduling problem with controllable processing times to minimize the total weighted completion time, focusing on the setting where a job's processing t…

cs.DS2024

Fair Repetitive Interval Scheduling

Klaus Heeger, Danny Hermelin, Yuval Itzhaki +2

Fair resource allocation is undoubtedly a crucial factor in customer satisfaction in several scheduling scenarios. This is especially apparent in repetitive scheduling models where…

cs.DS2024

Minimizing the Number of Tardy Jobs with Uniform Processing Times on Parallel Machines

Klaus Heeger, Hendrik Molter

In this work, we study the computational (parameterized) complexity of . Here, we are given identical parallel machines and jobs with…

cs.DS2024★ 2 cited

Minimizing the Number of Tardy Jobs and Maximal Tardiness on a Single Machine is NP-hard

Klaus Heeger, Danny Hermelin, Michael L. Pinedo +1

This paper resolves a long-standing open question in bicriteria scheduling regarding the complexity of a single machine scheduling problem which combines the number of tardy jobs a…

cs.DS2024

Fully Polynomial-time Algorithms Parameterized by Vertex Integrity Using Fast Matrix Multiplication

Matthias Bentert, Klaus Heeger, Tomohiro Koana

We study the computational complexity of several polynomial-time-solvable graph problems parameterized by vertex integrity, a measure of a graph's vulnerability to vertex removal i…

cs.DS2024

Minimizing the Weighted Number of Tardy Jobs is W[1]-hard

Klaus Heeger, Danny Hermelin

We consider the problem, the problem of minimizing the weighted number of tardy jobs on a single machine. This problem is one of the most basic and fundamental pr…

cs.DS2023

No Polynomial Kernels for Knapsack

Klaus Heeger, Danny Hermelin, Matthias Mnich +1

This paper focuses on kernelization algorithms for the fundamental Knapsack problem. A kernelization algorithm (or kernel) is a polynomial-time reduction from a problem onto itself…

cs.DS2023★ 2 cited

Threshold Testing and Semi-Online Prophet Inequalities

Martin Hoefer, Kevin Schewior

We study threshold testing, an elementary probing model with the goal to choose a large value out of i.i.d. random variables. An algorithm can test each variable once for…

cs.DS2023

Parameterized Lower Bounds for Problems in P via Fine-Grained Cross-Compositions

Klaus Heeger, André Nichterlein, Rolf Niedermeier

We provide a general framework to exclude parameterized running times of the form for problems that have polynomial running time lower bounds under hypotheses from…

cs.DS2021★ 1 cited

Popular matchings with weighted voters

Klaus Heeger, Ágnes Cseh

In the Popular Matching problem, we are given a bipartite graph and for each vertex , strict preferences over the neighbors of . Given two matc…

cs.DS2019★ 2 cited

Length-Bounded Cuts: Proper Interval Graphs and Structural Parameters

Matthias Bentert, Klaus Heeger, Dušan Knop

In the presented paper we study the Length-Bounded Cut problem for special graph classes as well as from a parameterized-complexity viewpoint. Here, we are given a graph , two v…