Study on MCM interconnect test generation using ant algorithm and particle swarm optimization algorithm

Abstract

A new approach based on ant algorithm (AA) and particle swarm optimization (PSO) algorithm is proposed for Multi-chip Module (MCM) interconnect test generation in this paper. Using the pheromone-updating rule and state transition rule, AA generates the initial candidate test vectors. PSO is employed to evolve the candidates generated by AA. The optimized search is guided by the swarm intelligent generated from cooperation and competition among particles of swarm, in order to get the best test vector with the high fault coverage. The international standard MCM benchmark circuit provided by the MCNC group was used to verify the approach. Comparing with the evolutionary algorithms and the deterministic algorithms, experimental results demonstrate that the approach can achieve high fault coverage and short execution time.