摘要
针对多品种小批量的物料生产中,由于实际需求量的不确定性,导致库存或者缺货造成资金积压或影响服务水平的情况,提出了用神经网络模型预测6类物料的需求。在3种不同的条件下,建立了相应的动态规划模型,通过求解这些模型得到各周物料的生产数量,并最终得出相应的生产安排。实践证明,该模型在保证客户满意度的前提下,减少了企业的库存,提高了企业的信誉,可为小批量物料制造企业提升市场竞争力提供参考。
In the production of multiple varieties and small batches of materials,due to the uncertainty of actual demand,inventory or out of stock can lead to capital accumulation or affect service levels.This article uses a neural network model to predict the demand for six types of materials,and establishes corresponding dynamic programming models under three different conditions.By solving these models,the production quantity of materials for each week is obtained,and the corresponding production arrangement is ultimately formed.Practice has proven that this model reduces the inventory of enterprises while ensuring customer satisfaction,improves their reputation,and can provide reference for small batch material manufacturing enterprises to enhance market competitiveness.
作者
颜姣姣
YAN Jiao-jiao(Zhejiang Institute of Communications,Hangzhou 311112,China)
出处
《浙江交通职业技术学院学报》
CAS
2023年第3期45-49,共5页
Journal of Zhejiang Institute of Communications
基金
2022年度高校国内访问学者“教师专业发展项目”(FX2022077)。
关键词
物料生产
神经网络
动态规划
生产安排
material production
neural network
dynamic programming
production arrangement
作者简介
颜姣姣(1983-),女,浙江杭州人,讲师,硕士,E-mail:yanjj@zjvtit.edu.cn。
