A MOGA-based approach for optimal analogue test points selection
Xiaomei Chen, Xiaofeng Meng, Bo Zhong, Hong Ji · International Journal of Modelling Identification and Control · 2010
Test point selection is one of the important topics for testability analysis. In this paper, a multi-objective genetic algorithm (MOGA)-based approach for optimal analogue test point selection is proposed. In this described method, redundancy deleting operator is used in Pareto frontier, crowding distances in objective space and decision space are combined, a new crossover operator based on Diff and an adaptive mutation operator is adopted, expecting to improve the exploration of the GA. Then the post-compromise is used to get a compromised optimal solution. Experiments on a practical example of analogue circuit and a series of hypothetical circuits indicate that the proposed method outperforms the other two existing methods, that is, entropy-based method and the GA-based method, in effectiveness and efficiency.