Title
An Optimization Approach of Ant Colony Algorithm and Adaptive Genetic Algorithm for MCM Interconnect Test
Abstract
An optimization approach based on ant colony algorithm (ACA) and adaptive genetic algorithm (AGA) is presented for the multi-chip module (MCM) interconnect test generation problem in this paper. The pheromone updating rule and state transition rule of ACA is designed for automatic test generation by combing the characteristics of MCM interconnect test. AGA generates the initial candidate test vectors by utilizing genetic operator. In order to get the best test vector with the high fault coverage, ACA is employed to evolve the candidates generated by AGA. The international standard MCM benchmark circuit was used to verify the approach. Comparing with not only the evolutionary algorithms, but also the deterministic algorithms, simulation results demonstrate that the hybrid algorithm can achieve high fault coverage, compact test set and short execution time.
Year
DOI
Venue
2009
10.1109/WGEC.2009.121
WGEC
Keywords
Field
DocType
evolutionary algorithm,integrated circuit testing,integrated circuit interconnections,state transition rule,automatic test generation,multichip modules,initial candidate test vector,mcm interconnect test,best test vector,automatic test pattern generation,ant colony algorithm,deterministic algorithm,#name?,compact test set,hybrid algorithm,high fault coverage,genetic algorithms,optimization approach,multichip module interconnect test generation,test generation problem,pheromone updating rule,adaptive genetic algorithm,electronic engineering computing,state transition,genetic operator,genetics,internal standard,optimization,fault coverage
Ant colony optimization algorithms,Test vector,Genetic operator,Automatic test pattern generation,Hybrid algorithm,Evolutionary algorithm,Fault coverage,Computer science,Algorithm,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
978-0-7695-3899-0
0
0.34
References 
Authors
5
2
Name
Order
Citations
PageRank
Chen Lei111.37
Quanhui Liu2243.16