Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Exact Algorithm for the One-Dimensional Quadratic Euclidean Cardinality-Weighted 2-Clustering with Given Center Problem. / Khandeev, Vladimir; Panasenko, Anna.
Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers. ред. / Yury Kochetov; Igor Bykadorov; Tatiana Gruzdeva. Springer Science and Business Media Deutschland GmbH, 2020. стр. 30-35 (Communications in Computer and Information Science; Том 1275 CCIS).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Exact Algorithm for the One-Dimensional Quadratic Euclidean Cardinality-Weighted 2-Clustering with Given Center Problem
AU - Khandeev, Vladimir
AU - Panasenko, Anna
N1 - Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - We consider a strongly NP-hard problem of clustering a finite set of points in Euclidean space into two clusters. In this problem, we find a partition of the input set minimizing the sum over both clusters of the weighted intracluster sums of the squared distances between the elements of the clusters and their centers. The weight factors are the cardinalities of the corresponding clusters and the centers are defined as follows. The center of the first cluster is unknown and determined as the centroid, while the center of the other one is given as input (is the origin without loss of generality). In this paper, we present a polynomial-time exact algorithm for the one-dimensional case of the problem.
AB - We consider a strongly NP-hard problem of clustering a finite set of points in Euclidean space into two clusters. In this problem, we find a partition of the input set minimizing the sum over both clusters of the weighted intracluster sums of the squared distances between the elements of the clusters and their centers. The weight factors are the cardinalities of the corresponding clusters and the centers are defined as follows. The center of the first cluster is unknown and determined as the centroid, while the center of the other one is given as input (is the origin without loss of generality). In this paper, we present a polynomial-time exact algorithm for the one-dimensional case of the problem.
KW - Euclidean space
KW - Exact algorithm
KW - Minimum sum-of-squares
KW - NP-hard problem
KW - One-dimensional case
KW - Polynomial-time
KW - Weighted clustering
UR - http://www.scopus.com/inward/record.url?scp=85092074622&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-58657-7_4
DO - 10.1007/978-3-030-58657-7_4
M3 - Conference contribution
AN - SCOPUS:85092074622
SN - 9783030586560
T3 - Communications in Computer and Information Science
SP - 30
EP - 35
BT - Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers
A2 - Kochetov, Yury
A2 - Bykadorov, Igor
A2 - Gruzdeva, Tatiana
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Mathematical Optimization Theory and Operations Research,MOTOR 2020
Y2 - 6 July 2020 through 10 July 2020
ER -
ID: 25674900