AI-based search techniques have been adapted as viable, topology-independen
t fault-tolerant routing strategies on multiprocessor networks [P.K.K. Loh,
Artificial intelligence search techniques as fault-tolerant routing strate
gies, Parallel Computing 22 (8) (1996) 1127-1147]. These fault-tolerant rou
ting strategies are viable with the exception that the routes obtained were
non-minimal. This meant that a large number of redundant node traversals w
ere made in reaching the destination, increasing the likelihood of encounte
ring further faulty network components. Here, we investigate the adaptation
of a genetic-heuristic algorithm combination as a fault-tolerant routing s
trategy. Our results show that this hybrid fault-tolerant routing strategy
produces minimal or near-minimal routes. Under certain fault conditions, th
is new strategy outperforms the heuristic AI-based ones with a significant
reduction in the number of redundant traversals. (C) 2001 Elsevier Science
B.V. All rights reserved.