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Optimization method for diagnostic sequence based on improved particle swarm optimization algorithm 被引量:7

Optimization method for diagnostic sequence based on improved particle swarm optimization algorithm
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摘要 To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization (QPSO) algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice. To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization (QPSO) algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第4期899-905,共7页 系统工程与电子技术(英文版)
基金 supported by the National Natural Science Foundation of China(60771063).
关键词 diagnostic sequence optimization design for testability intelligent optimization QPSO algorithm diagnostic sequence optimization, design for testability, intelligent optimization, QPSO algorithm
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