Intelligent safety inventory prediction model and its application in chemical fiber enterprises

Abstract

Accurate and timely prediction of safety stock is of great significance to reduce costs and improve economic efficiency. It is a problem that needs to be solved urgently in the manufacturing industry. Because there is a complex nonlinear relationship between factors that affect the safety inventory, it is difficult to obtain better prediction results with traditional methods. This paper presents an intelligent safety inventory prediction model based on artificial fish swarm algorithm and applies it to inventory management of Quanzhou chemical fiber enterprises. The research has important theoretical and practical significance for the inventory management of chemical fiber enterprises and even private enterprises.