Economic design of &Xmacr; control chart using genetic algorithm and simulated annealing algorithm

Control charts are very popular for monitoring production processes and designed economically to achieve minimum quality costs. This paper focuses on evaluating the performance of genetic algorithm (GA) and simulated annealing algorithm (SAA) in economical design of &Xmacr; control chart. The performances of GA and SAA is demonstrated through a numerical example and the results were compared with Montgomery (1982). To outperform Montgomery's approach the paper dealt with the same example and demonstrate its utility. Duncan model of single assignable cause without taking into account process improvement and statistical properties is adopted to formulate the cost minimising equation and the computation is achieved through Simpson's one‐third approximation rule. A comparison between the performance of GA and SAA is also exhibited in this paper.