Study on Mcm Test Scheme Using Adaptive Genetic Algorithm and Particle Swarm Optimization Algorithm

The paper presents a new interconnect test generation scheme based on adaptive genetic algorithm (AGA) and particle swarm optimization algorithm (PSO) for Multi-chip Module (MCM) applications. By combing the characteristics of interconnect test and constructing particle expression of test generation, the velocity updating equation and position updating equation of discrete PSO are presented in this paper. AGA generates the initial candidate test vectors in this scheme. In order to improve the fault coverage of the test vector, PSO is employed to evolve the candidates generated by AGA. The international standard MCM benchmark circuit was used to verify the scheme. Comparing with not only the evolutionary algorithms, but also the deterministic algorithms, simulation results demonstrate that the hybrid scheme can achieve high fault coverage, short CPU time and compact test set, which shows that it is a novel optimized method deserving research.