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.
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