Research on Production Decision Making Based on Differential Evolutionary Algorithms and Optimisation Models

Abstract

In this paper, the problem of defect detection and production decision-making in the production process of electronic products is studied in depth. The optimization model and differential evolutionary algorithm are used to solve the challenges of quality control and cost optimization. Firstly, this paper proposes a defect detection scheme based on statistical sampling and hypothesis testing, which optimizes the sample detection cost; secondly, this paper constructs a production cost optimization model based on the defective rate of spare parts and the detection cost, and derives the optimal decision-making scheme under different strategies using differential evolution algorithms; lastly, this paper further extends the model and optimizes the production flow to address the cost optimization problem in a multi-process production process, which indicates that the quality control and cost optimization problems in electronic products production are solved. Finally, this paper further extends the model and optimizes the production process for the cost optimization problem in the multi-process production process, and the results show that the model can effectively reduce the production cost and improve the decision-making efficiency.