In this paper, genetic algorithms are applied to solve the error-correcting subgraph isomorphism (ECSI) problems. The error-correcting subgraph isomorphism problems are first formulated as permutation searching problems. Two ECSI algorithms are devised. The first algorithm implements pure genetic algorithms with permutation representation. The second is a hybrid algorithm that amalgamates assignment algorithms and local search strategy to improve convergence speed. From experiments, the second algorithm shows better performance than the first one and also reveals that the approach is superior to traditional tree search approach.
|Number of pages||5|
|State||Published - 1995|
|Event||Proceedings of the 1995 IEEE International Conference on Evolutionary Computation. Part 1 (of 2) - Perth, Aust|
Duration: 29 Nov 1995 → 1 Dec 1995
|Conference||Proceedings of the 1995 IEEE International Conference on Evolutionary Computation. Part 1 (of 2)|
|Period||29/11/95 → 1/12/95|