AI-based search techniques have been adapted as viable, topology--independent fault--tolerant routing strategies on multipro- cessor networks [PK.K. Loh, Artificial intelligence search techniques as fault-tolerant routing strategies, Parallel Computing 22 (8) (1996) l l27--1 l47]. These fault-tolerant routing strategies are viable with the exception that the routes obtained were non--minimal. This meant that a large number of redundant node traversals were made in reaching the destination, increasing the likelihood of encountering further faulty network components. Here, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault--tolerant routing strategy. Our results show that this hybrid fault--tolerant routing strategy produces minimal or near-minimal routes. Under certain fault conditions, this new strategy outperforms the heuristic AI--based ones with a significant reduction in the number of redundant traversals.
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