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Maximum diversity problem with squared euclidean distance. / Eremeev, Anton V.; Kel’manov, Alexander V.; Kovalyov, Mikhail Y. и др.

Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. ред. / Michael Khachay; Panos Pardalos; Yury Kochetov. Springer-Verlag GmbH and Co. KG, 2019. стр. 541-551 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11548 LNCS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Eremeev, AV, Kel’manov, AV, Kovalyov, MY & Pyatkin, AV 2019, Maximum diversity problem with squared euclidean distance. в M Khachay, P Pardalos & Y Kochetov (ред.), Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 11548 LNCS, Springer-Verlag GmbH and Co. KG, стр. 541-551, 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019, Ekaterinburg, Российская Федерация, 08.07.2019. https://doi.org/10.1007/978-3-030-22629-9_38

APA

Eremeev, A. V., Kel’manov, A. V., Kovalyov, M. Y., & Pyatkin, A. V. (2019). Maximum diversity problem with squared euclidean distance. в M. Khachay, P. Pardalos, & Y. Kochetov (Ред.), Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings (стр. 541-551). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11548 LNCS). Springer-Verlag GmbH and Co. KG. https://doi.org/10.1007/978-3-030-22629-9_38

Vancouver

Eremeev AV, Kel’manov AV, Kovalyov MY, Pyatkin AV. Maximum diversity problem with squared euclidean distance. в Khachay M, Pardalos P, Kochetov Y, Редакторы, Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. Springer-Verlag GmbH and Co. KG. 2019. стр. 541-551. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-22629-9_38

Author

Eremeev, Anton V. ; Kel’manov, Alexander V. ; Kovalyov, Mikhail Y. и др. / Maximum diversity problem with squared euclidean distance. Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. Редактор / Michael Khachay ; Panos Pardalos ; Yury Kochetov. Springer-Verlag GmbH and Co. KG, 2019. стр. 541-551 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{3dfc58d092a94a4caf5b846ba7411f3c,
title = "Maximum diversity problem with squared euclidean distance",
abstract = "In this paper we consider the following Maximum Diversity Subset problem. Given a set of points in Euclidean space, find a subset of size M maximizing the squared Euclidean distances between the chosen points. We propose an exact dynamic programming algorithm for the case of integer input data. If the dimension of the Euclidean space is bounded by a constant, the algorithm has a pseudo-polynomial time complexity. Using this algorithm, we develop an FPTAS for the special case where the dimension of the Euclidean space is bounded by a constant. We also propose a new proof of strong NP-hardness of the problem in the general case.",
keywords = "Euclidean space, Exact algorithm, Fixed space dimension, Given size, Integer instance, Maximum variance, Pseudo-polynomial time, Strong NP-hardness, Subset of points, ALGORITHMS, SUBSET",
author = "Eremeev, {Anton V.} and Kel{\textquoteright}manov, {Alexander V.} and Kovalyov, {Mikhail Y.} and Pyatkin, {Artem V.}",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-22629-9_38",
language = "English",
isbn = "9783030226282",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag GmbH and Co. KG",
pages = "541--551",
editor = "Michael Khachay and Panos Pardalos and Yury Kochetov",
booktitle = "Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings",
address = "Germany",
note = "18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019 ; Conference date: 08-07-2019 Through 12-07-2019",

}

RIS

TY - GEN

T1 - Maximum diversity problem with squared euclidean distance

AU - Eremeev, Anton V.

AU - Kel’manov, Alexander V.

AU - Kovalyov, Mikhail Y.

AU - Pyatkin, Artem V.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - In this paper we consider the following Maximum Diversity Subset problem. Given a set of points in Euclidean space, find a subset of size M maximizing the squared Euclidean distances between the chosen points. We propose an exact dynamic programming algorithm for the case of integer input data. If the dimension of the Euclidean space is bounded by a constant, the algorithm has a pseudo-polynomial time complexity. Using this algorithm, we develop an FPTAS for the special case where the dimension of the Euclidean space is bounded by a constant. We also propose a new proof of strong NP-hardness of the problem in the general case.

AB - In this paper we consider the following Maximum Diversity Subset problem. Given a set of points in Euclidean space, find a subset of size M maximizing the squared Euclidean distances between the chosen points. We propose an exact dynamic programming algorithm for the case of integer input data. If the dimension of the Euclidean space is bounded by a constant, the algorithm has a pseudo-polynomial time complexity. Using this algorithm, we develop an FPTAS for the special case where the dimension of the Euclidean space is bounded by a constant. We also propose a new proof of strong NP-hardness of the problem in the general case.

KW - Euclidean space

KW - Exact algorithm

KW - Fixed space dimension

KW - Given size

KW - Integer instance

KW - Maximum variance

KW - Pseudo-polynomial time

KW - Strong NP-hardness

KW - Subset of points

KW - ALGORITHMS

KW - SUBSET

UR - http://www.scopus.com/inward/record.url?scp=85067677029&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-22629-9_38

DO - 10.1007/978-3-030-22629-9_38

M3 - Conference contribution

AN - SCOPUS:85067677029

SN - 9783030226282

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 541

EP - 551

BT - Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings

A2 - Khachay, Michael

A2 - Pardalos, Panos

A2 - Kochetov, Yury

PB - Springer-Verlag GmbH and Co. KG

T2 - 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019

Y2 - 8 July 2019 through 12 July 2019

ER -

ID: 20643987