Premium
Local search metaheuristics for the critical node problem
Author(s) -
Aringhieri Roberto,
Grosso Andrea,
Hosteins Pierre,
Scatamacchia Rosario
Publication year - 2016
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.21671
Subject(s) - metaheuristic , iterated local search , graph , computer science , node (physics) , mathematical optimization , exploit , iterated function , local search (optimization) , set (abstract data type) , variable neighborhood search , mathematics , theoretical computer science , mathematical analysis , computer security , structural engineering , engineering , programming language
We present two metaheuristics for the Critical Node Problem, that is, the maximal fragmentation of a graph through the deletion of k nodes. The two metaheuristics are based on the Iterated Local Search and Variable Neighborhood Search frameworks. Their main characteristic is to exploit two smart and computationally efficient neighborhoods which we show can be implemented far more efficiently than the classical neighborhood based on the exchange of any two nodes in the graph, and which we prove is equivalent to the classical neighborhood in the sense that it yields the same set of neighbors. Solutions to improve the overall running time without deteriorating the quality of the solution computed are also illustrated. The results of the proposed metaheuristics outperform those currently available in literature. © 2016 Wiley Periodicals, Inc. NETWORKS, Vol. 67(3), 209–221 2016