Title: A MOGA-based approach for optimal analogue test points selection

Authors: Xiaomei Chen, Xiaofeng Meng, Bo Zhong, Hong Ji

Addresses: College of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing, 100083, China; Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing, 102206, China. ' College of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing, 100083, China. ' College of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing, 100083, China. ' College of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing, 100083, China

Abstract: 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.

Keywords: analogue circuits; combinatorial optimisation; multi-objective optimisation; testability analysis; test point selection; multi-objective genetic algorithms; MOGA.

DOI: 10.1504/IJMIC.2010.032372

International Journal of Modelling, Identification and Control, 2010 Vol.9 No.1/2, pp.144 - 151

Available online: 01 Apr 2010 *

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