Three-stage greedy and neural-network approach for subgraph isomorphism problem

N. Funabiki, J. Kitamichi

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


This paper presents a three-stage greedy and neural-network algorithm for the subgraph isomorphism problem. Given two graphs of G = (V1, E1) and H = (V2, E2), the goal of this NP-complete problem is to find a subgraph of H isomorphic to G. The proposed algorithm consists of three stages. The first stage extracts a set of vertices in H which may be assigned to each vertex in G, based on the newly defined necessary condition. The second stage sequentially seeks a solution based on a greedy method by assigning each vertex in G to a vertex in H satisfying the constraints in descending order of degrees. After the second stage fails at all, the third stage resolves the constraints in parallel based on a digital neural network, where the best result in the second stage is partially adopted to reduce the search space. The performance is evaluated by solving randomly generated graph instances, where the simulation results show that our algorithm achieves the high solution quality in reasonable computation time.

Original languageEnglish
Pages (from-to)1892-1897
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1998
Externally publishedYes
EventProceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 2 (of 5) - San Diego, CA, USA
Duration: Oct 11 1998Oct 14 1998

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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