多基地煤焦油加工企业产销计划优化探讨  

Optimization of Production and Marketing Plan of Multi Base Coal Tar Processing Enterprises

作　　者：王焕煜 戴鸣 Wang Huanyu;Dai Ming(Baowu Carbon Technology Co.,Ltd.,Shanghai 201999,China)

机构地区：[1]宝武碳业科技股份有限公司,上海201999

出　　处：《广东化工》2022年第8期102-105,共4页Guangdong Chemical Industry

摘　　要：为发挥多生产基地多产品供应全国各地用户企业的优势,探讨利用线性规划模型进行供应链的计划层优化。改进模型,采用分别处理自产和外购原料焦油的虚拟装置叠加来模拟实际生产装置,消除模型系数与决策变量的关联,使模型变回线性方便求解。采用改进的线性规划模型,数据通过Excel表输入输出,并用Python提高数据处理能力和自动化程度,以公司四个基地生产的六个产品为例,优化得到全局最优的产品流向方案和生产计划,降低了产品运输的成本,并使产品加工费用、原料费用低的生产基地优先发挥生产装置的产能;提高了企业利润,也带来低碳化的社会效益,值得推广应用,尤其在多生产基地的企业。In order to take the advantages of our enterprise’s multi production bases and multi product customers all over the country, a linear programming model based planning optimization for supply chain was discussed. In the modified model, the virtual plant in which self-produced and purchased raw tar are superimposed can simulate the actual production plants. The correlation between model coefficients and decision variables is eliminated, so the model is changed back to linear and easy to solve. When the linear programming model is processed, the data is input and output through Excel, and Python is used to improve the data processing ability and automation. Taking six products from four bases(Baowu Carbon Technology Co., Ltd.) as an example, the model optimizes our marketing and production plan on the whole. It reduces the product transportation cost, and makes the production bases with lower product processing cost and raw material cost enhance their production capacity. It could create higher profits for enterprises and brings low-carbon social benefits as well. This model is worth promoting and applying, especially in enterprises with multiple production bases.

关 键 词：生产计划 优化 线性规划 供应链 PYTHON 

分 类 号：F426.7[经济管理—产业经济] TQ522.6[化学工程—煤化学工程]