A DEA-bases Approach for Multi-objective Design of Attribute Acceptance Sampling Plans

Acceptance sampling (AS), as one of the main fields of statistical quality control (SQC),involves a system of principles and methods to make decisions about accepting or rejecting alot or sample. For attributes, the design of a single AS plan generally requires determination ofsample size, and acceptance number. Numerous approaches have been developed foroptimally selection of design parameters in last decades. We develop a multi-objectiveeconomic-statistical design (MOESD) of the single AS plan to reach a well-balancedcompromise between cost and quality features. Moreover, a simple and efficient DEA-basedalgorithm for solving the model is proposed. Through a simulation study, the efficiency ofproposed model is illustrated. Comparisons of optimal designs obtained using MOESD toeconomic model with statistical constraints reveals enhanced performance of the multiobjectivemodel.