Variable neighborhood search for the heaviest k-subgraph

Jack Brimberg; Nenad Mladenović; Dragan Urošević; Wai Ting Ngai

doi:10.1016/j.cor.2008.12.020

Variable neighborhood search for the heaviest k-subgraph

Jack Brimberg, Nenad Mladenović, Dragan Urošević, Wai Ting Ngai

Research output: Journal article publication › Journal article › Academic research › peer-review

55 Citations (Scopus)

Abstract

This paper presents a variable neighborhood search (VNS) heuristic for solving the heaviest k-subgraph problem. Different versions of the heuristic are examined including 'skewed' VNS and a combination of a constructive heuristic followed by VNS. Extensive computational experiments are performed on a series of large random graphs as well as several instances of the related maximum diversity problem taken from the literature. The results obtained by VNS were consistently the best over a number of other heuristics tested.

Original language	English
Pages (from-to)	2885-2891
Number of pages	7
Journal	Computers and Operations Research
Volume	36
Issue number	11
DOIs	https://doi.org/10.1016/j.cor.2008.12.020
Publication status	Published - 1 Nov 2009

Keywords

Combinatorial optimization
Heaviest k-subgraph
Maximum diversity
Metaheuristics
Variable neighborhood search

ASJC Scopus subject areas

General Computer Science
Modelling and Simulation
Management Science and Operations Research

More information

10.1016/j.cor.2008.12.020

Cite this

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abstract = "This paper presents a variable neighborhood search (VNS) heuristic for solving the heaviest k-subgraph problem. Different versions of the heuristic are examined including 'skewed' VNS and a combination of a constructive heuristic followed by VNS. Extensive computational experiments are performed on a series of large random graphs as well as several instances of the related maximum diversity problem taken from the literature. The results obtained by VNS were consistently the best over a number of other heuristics tested.",

keywords = "Combinatorial optimization, Heaviest k-subgraph, Maximum diversity, Metaheuristics, Variable neighborhood search",

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AU - Mladenović, Nenad

AU - Urošević, Dragan

AU - Ngai, Wai Ting

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AB - This paper presents a variable neighborhood search (VNS) heuristic for solving the heaviest k-subgraph problem. Different versions of the heuristic are examined including 'skewed' VNS and a combination of a constructive heuristic followed by VNS. Extensive computational experiments are performed on a series of large random graphs as well as several instances of the related maximum diversity problem taken from the literature. The results obtained by VNS were consistently the best over a number of other heuristics tested.

KW - Combinatorial optimization

KW - Heaviest k-subgraph

KW - Maximum diversity

KW - Metaheuristics

KW - Variable neighborhood search

UR - https://www.scopus.com/pages/publications/64849113019

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DO - 10.1016/j.cor.2008.12.020

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JF - Computers and Operations Research

IS - 11

ER -

Variable neighborhood search for the heaviest k-subgraph

Abstract

Keywords

ASJC Scopus subject areas

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