activity
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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8 papers · 1 filter

cs.GT2022

A Map of Diverse Synthetic Stable Roommates Instances

Niclas Boehmer, Klaus Heeger, Stanisław Szufa

Focusing on Stable Roommates (SR) instances, we contribute to the toolbox for conducting experiments for stable matching problems. We introduce a polynomial-time computable pseudom…

cs.GT2022

Deepening the (Parameterized) Complexity Analysis of Incremental Stable Matching Problems

Niclas Boehmer, Klaus Heeger, Rolf Niedermeier

When computing stable matchings, it is usually assumed that the preferences of the agents in the matching market are fixed. However, in many realistic scenarios, preferences change…

cs.GT2022

Stable Matching with Multilayer Approval Preferences: Approvals can be Harder than Strict Preferences

Matthias Bentert, Niclas Boehmer, Klaus Heeger +1

We study stable matching problems where agents have multilayer preferences: There are layers each consisting of one preference relation for each agent. Recently, Chen et al.…

cs.GT2022★ 1 cited

Adapting Stable Matchings to Forced and Forbidden Pairs

Niclas Boehmer, Klaus Heeger

We introduce the problem of adapting a stable matching to forced and forbidden pairs. Specifically, given a stable matching , a set of forced pairs, and a set of forbi…

cs.GT2022

Multivariate Algorithmics for Eliminating Envy by Donating Goods

Niclas Boehmer, Robert Bredereck, Klaus Heeger +2

Fairly dividing a set of indivisible resources to a set of agents is of utmost importance in some applications. However, after an allocation has been implemented the preferences of…

cs.GT2021★ 1 cited

Theory of and Experiments on Minimally Invasive Stability Preservation in Changing Two-Sided Matching Markets

Niclas Boehmer, Klaus Heeger, Rolf Niedermeier

Following up on purely theoretical work of Bredereck et al. [AAAI 2020], we contribute further theoretical insights into adapting stable two-sided matchings to change. Moreover, we…

cs.GT2020

A Fine-Grained View on Stable Many-To-One Matching Problems with Lower and Upper Quotas

Niclas Boehmer, Klaus Heeger

In the Hospital Residents problem with lower and upper quotas (), the goal is to find a stable matching of residents to hospitals where the number of residents matched to…

cs.GT2020

Bribery and Control in Stable Marriage

Niclas Boehmer, Robert Bredereck, Klaus Heeger +1

We initiate the study of external manipulations in Stable Marriage by considering several manipulative actions as well as several manipulation goals. For instance, one goal is to m…