Particle swarm optimization for the economic and economic statistical designs of the control chart

Authors:
Mingchang Chih;Li-Lun Yeh;Feng-Chia Li
Affiliations:
Office of Cross-Strait Exchange, Industrial Technology Research Institute, Chutung, Hsinchu 31040, Taiwan, ROC;Department of Business Adminstration Hwa Hsia Institute of Technology, No.111, Gongzhuan Rd., Zhonghe, Taipei, Taiwan 235, ROC;Department of Information Management, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 35664, Taiwan, ROC
Venue:
Applied Soft Computing
Year:
2011

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Abstract

The economic and economic statistical designs of an X@? control chart comprise the constrained optimization problem, which involves the simultaneous use of continuous and discrete decision variables. The particle swarm optimization (PSO) technique is adapted to deal with both continuous and discrete variables as required by the optimization problem. A numerical example in the study of Rahim and Banerjee (1993) [13], which used the Gamma failure mechanism, is used in the current study to indicate the procedure for solving the PSO algorithm performance. The results are compared with those from Genetic Algorithm, a popular evolutionary technique in the field of control charts under the same conditions. PSO is found to be a promising method for solving the problems of inherent in the economic and economic statistical designs of an X@? control chart.