TY - GEN
T1 - Multidimensional Stable Roommates with Master List
AU - Bredereck, Robert
AU - Heeger, Klaus
AU - Knop, Dušan
AU - Niedermeier, Rolf
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Since the early days of research in algorithms and complexity, the computation of stable matchings is a core topic. While in the classic setting the goal is to match up two agents (either from different “gender” (this is Stable Marriage) or “unrestricted” (this is Stable Roommates)), Knuth [1976] triggered the study of three- or multidimensional cases. Here, we focus on the study of Multidimensional Stable Roommates, known to be NP-hard since the early 1990’s. Many NP-hardness results, however, rely on very general input instances that do not occur in at least some of the specific application scenarios. With the quest for identifying islands of tractability, we look at the case of master lists. Here, as natural in applications where agents express their preferences based on “objective” scores, one roughly speaking assumes that all agent preferences are “derived from” a central master list, implying that the individual agent preferences shall be similar. Master lists have been frequently studied in the two-dimensional (classic) stable matching case, but seemingly almost never for the multidimensional case. This work, also relying on methods from parameterized algorithm design and complexity analysis, performs a first systematic study of Multidimensional Stable Roommates under the assumption of master lists.
AB - Since the early days of research in algorithms and complexity, the computation of stable matchings is a core topic. While in the classic setting the goal is to match up two agents (either from different “gender” (this is Stable Marriage) or “unrestricted” (this is Stable Roommates)), Knuth [1976] triggered the study of three- or multidimensional cases. Here, we focus on the study of Multidimensional Stable Roommates, known to be NP-hard since the early 1990’s. Many NP-hardness results, however, rely on very general input instances that do not occur in at least some of the specific application scenarios. With the quest for identifying islands of tractability, we look at the case of master lists. Here, as natural in applications where agents express their preferences based on “objective” scores, one roughly speaking assumes that all agent preferences are “derived from” a central master list, implying that the individual agent preferences shall be similar. Master lists have been frequently studied in the two-dimensional (classic) stable matching case, but seemingly almost never for the multidimensional case. This work, also relying on methods from parameterized algorithm design and complexity analysis, performs a first systematic study of Multidimensional Stable Roommates under the assumption of master lists.
UR - http://www.scopus.com/inward/record.url?scp=85097894592&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-64946-3_5
DO - 10.1007/978-3-030-64946-3_5
M3 - Conference contribution
AN - SCOPUS:85097894592
SN - 9783030649456
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 59
EP - 73
BT - Web and Internet Economics - 16th International Conference, WINE 2020, Proceedings
A2 - Chen, Xujin
A2 - Gravin, Nikolai
A2 - Hoefer, Martin
A2 - Mehta, Ruta
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference on Web and Internet Economics, WINE 2020
Y2 - 7 December 2020 through 11 December 2020
ER -