Study on the Production Decision by Dynamic Programming and Nonlinear Programming

Abstract

An excellent production decision-making plan is the fundamental guarantee for a company to operate continuously and generate profits. This paper aims to establish a decision-making model by using csampling inspection, dynamic optimization and nonlinear programming, and provide the optimal solution through boundary conditions and constraints, so as to realize the optimization of production decision-making. This paper first establishes a hypothesis testing model, using different testing methods for various sample sizes to determine the minimum sample size at a given confidence level. Then, through simulation experiments, the sampling strategy is optimized, and the defect rate and confidence interval are provided. Subsequently, by combining dynamic programming and nonlinear 0-1 programming, and considering the mutual influence between processes, the production flow of multi-stage processes and spare parts is optimized, resulting in the optimal production procedure. The findings of this study provide effective references for decision optimization in complex production conditions, offering significant practical application value.