Determination of optimal inspection sequence within misclassification error bound

The objective of this paper is to formulate a model, integrating the branch and bound and Lagrangian relaxation, to minimize two major types of inspection errors and their subsequent misclassification penalties for the benefits of both producers and consumers. The results show the proposed model is effective and computationally feasible when adopted to select the optimal inspection sequence from a group of viable sequences. The model can be expected to generate significant contributions to both the academic field and the real-world practice of quality control.