Research on Multi-process Production Decision Optimization Based on Genetic Algorithm

Abstract

This paper studies the decision optimization problem in the multi-process production process of an enterprise in the production of best-selling electronic products. Aiming at the assembly process of two kinds of key parts, this paper uses genetic algorithm, exhaustion method and other theories and methods to optimize it with the product multi-process production process. By establishing the decision model, the problems of calculating the number of sampling inspection under the condition of nominal value, making the optimal decision in the production process of the enterprise, the global optimal detection and processing decision under the condition of multi-process production, as well as recalculating the defective rate and solving it again through sampling inspection are solved respectively. The results show that the proposed model and method can significantly reduce the production cost and increase the profits of enterprises.