Paper Info
Title
A hybrid heuristic for the maximum clique problem
Abstract
In this paper we present a heuristic based steady-state genetic algorithm for the maximum clique problem. The steady-state genetic algorithm generates cliques, which are then extended into maximal cliques by the heuristic. We compare our algorithm with three best evolutionary approaches and the overall best approach, which is non-evolutionary, for the maximum clique problem and find that our algorithm outperforms all the three evolutionary approaches in terms of best and average clique sizes found on majority of DIMACS benchmark instances. However, the obtained results are much inferior to those obtained with the best approach for the maximum clique problem.
Year
DOI
Venue
2006
10.1007/s10732-006-3750-x
J. Heuristics
Keywords
Field
DocType
Combinatorial optimization,Greedy heuristic,Maximum clique,Steady-state genetic algorithm
Artificial intelligence,Genetic algorithm,Clique problem,Steady state genetic algorithm,Mathematical optimization,Heuristic,Combinatorics,Maximum common subgraph isomorphism problem,Clique,Greedy algorithm,Combinatorial optimization,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
12
1-2
1381-1231
Citations 
PageRank 
References 
24
1.04
24
Authors
2
Name
Order
Citations
PageRank
Alok Singh120117.15
Ashok Kumar Gupta2352.67