Variable neighborhood search for the heaviest k-subgraph

Authors:
Jack Brimberg;Nenad Mladenović;Dragan Urošević;Eric Ngai
Affiliations:
Department of Business Administration, Royal Military College of Canada, Kingston, Ontario, Canada and GERAD;School of Mathematics, Brunel University, West London, Uxbridge, UB8 3PH, UK.;Mathematical Institute, Serbian Academy of Sciences, Belgrade, Yugoslavia;Department of Management and Marketing, The Hong Kong Polytechnic University, Hong Kong, China
Venue:
Computers and Operations Research
Year:
2009

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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.