Abstract
This paper concerned with applying suggested mathematical programming and nonlinear goal programming models to determine the producer's risk (α), consumer's risk (β) and acceptance level (c) simultaneously. The suggested nonlinear goal programming model allowed α and β values to be free and determined their values more accurately which make balance between the power of a statistical test (1-β) and level of significance α. Real quality control data are used to evaluate the performance of the suggested models . This enables decision makers in quality control to develop more accurate and free acceptance sampling plans.