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Variable neighborhood search variants for Min-power symmetric connectivity problem. / Erzin, A. I.; Mladenovic, N.; Plotnikov, R. V.

In: Computers and Operations Research, Vol. 78, 01.02.2017, p. 557-563.

Research output: Contribution to journal › Article › peer-review

Harvard

Erzin, AI, Mladenovic, N & Plotnikov, RV 2017, 'Variable neighborhood search variants for Min-power symmetric connectivity problem', Computers and Operations Research, vol. 78, pp. 557-563. https://doi.org/10.1016/j.cor.2016.05.010

APA

Erzin, A. I., Mladenovic, N., & Plotnikov, R. V. (2017). Variable neighborhood search variants for Min-power symmetric connectivity problem. Computers and Operations Research, 78, 557-563. https://doi.org/10.1016/j.cor.2016.05.010

Vancouver

Erzin AI, Mladenovic N, Plotnikov RV. Variable neighborhood search variants for Min-power symmetric connectivity problem. Computers and Operations Research. 2017 Feb 1;78:557-563. doi: 10.1016/j.cor.2016.05.010

Author

Erzin, A. I. ; Mladenovic, N. ; Plotnikov, R. V. / Variable neighborhood search variants for Min-power symmetric connectivity problem. In: Computers and Operations Research. 2017 ; Vol. 78. pp. 557-563.

BibTeX

@article{0a63335806e14db684d9ed6f07fab320,
title = "Variable neighborhood search variants for Min-power symmetric connectivity problem",
abstract = "We consider the problem of optimal communication tree construction in a given undirected weighted graph. Such a problem occurs while minimizing the power consumption of data transmission in different distributed networks in the case when network elements are able to adjust their transmission ranges. In this paper, the most general strongly NP-hard formulation, when edge weights have arbitrary non-negative values, is considered. We propose new heuristics, mostly based on variable neighborhood search, for getting an approximate solution of the problem. Extensive comparative analysis between the proposed methods was performed. Numerical experiments demonstrated the high efficiency of the proposed heuristics.",
keywords = "Energy efficiency, NP-hard problem, Variable neighborhood search, Wireless sensor network, RADIO NETWORKS, ASSIGNMENT",
author = "Erzin, {A. I.} and N. Mladenovic and Plotnikov, {R. V.}",
note = "Publisher Copyright: {\textcopyright} 2016 Elsevier Ltd",
year = "2017",
month = feb,
day = "1",
doi = "10.1016/j.cor.2016.05.010",
language = "English",
volume = "78",
pages = "557--563",
journal = "Computers and Operations Research",
issn = "0305-0548",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Variable neighborhood search variants for Min-power symmetric connectivity problem

AU - Erzin, A. I.

AU - Mladenovic, N.

AU - Plotnikov, R. V.

N1 - Publisher Copyright: © 2016 Elsevier Ltd

PY - 2017/2/1

Y1 - 2017/2/1

N2 - We consider the problem of optimal communication tree construction in a given undirected weighted graph. Such a problem occurs while minimizing the power consumption of data transmission in different distributed networks in the case when network elements are able to adjust their transmission ranges. In this paper, the most general strongly NP-hard formulation, when edge weights have arbitrary non-negative values, is considered. We propose new heuristics, mostly based on variable neighborhood search, for getting an approximate solution of the problem. Extensive comparative analysis between the proposed methods was performed. Numerical experiments demonstrated the high efficiency of the proposed heuristics.

AB - We consider the problem of optimal communication tree construction in a given undirected weighted graph. Such a problem occurs while minimizing the power consumption of data transmission in different distributed networks in the case when network elements are able to adjust their transmission ranges. In this paper, the most general strongly NP-hard formulation, when edge weights have arbitrary non-negative values, is considered. We propose new heuristics, mostly based on variable neighborhood search, for getting an approximate solution of the problem. Extensive comparative analysis between the proposed methods was performed. Numerical experiments demonstrated the high efficiency of the proposed heuristics.

KW - Energy efficiency

KW - NP-hard problem

KW - Variable neighborhood search

KW - Wireless sensor network

KW - RADIO NETWORKS

KW - ASSIGNMENT

UR - http://www.scopus.com/inward/record.url?scp=84973532114&partnerID=8YFLogxK

U2 - 10.1016/j.cor.2016.05.010

DO - 10.1016/j.cor.2016.05.010

M3 - Article

AN - SCOPUS:84973532114

VL - 78

SP - 557

EP - 563

JO - Computers and Operations Research

JF - Computers and Operations Research

SN - 0305-0548

ER -

ID: 10321757