Single-Objective Optimization Based on 0-1 Programming

This paper addresses the problem of ensuring high product standards and cost-effectiveness in quality control in enterprise production. We investigate the decision-making strategies under various scenarios such as sampling and testing programme design, judgement programme selection, production process optimisation and error analysis. The variability in testing costs in each process and the uncertainty of product qualification rate increase the difficulty of planning for cost control. In order to solve these problems, this paper divides the inspection scenarios into two categories: small sample and large sample, and assumes the changes of variables such as defective rate and market exchange rate, constructs a decision tree model to cover each stage, and defines the key parameters through 0-1 programming to form a comprehensive decision-making framework. A single-objective optimization model is developed by solving different scenarios using binomial and normal distributions. In addition, to assess the robustness of the model, a series of robustness tests were conducted to verify the applicability and accuracy of the model. The data results show that the developed model can maximise the profit of the enterprise in all situations. The framework provides actionable insights for quality control in manufacturing industries.