Research on Optimization of Ordering and Transportation Strategy based on TOPSIS and Time Series Model
Jiayu Zhang, Yingwu Li, Su Li · Advances in economics, business and management research/Advances in Economics, Business and Management Research · 2022
The ordering and transportation of raw materials is a crucial process for enterprises to produce and receive receivables, so it is necessary to study this process pertinently.This paper studies the ordering and transportation of raw materials in production enterprises.The problem of ordering and transportation of raw materials needs to make use of relevant materials and information such as the order quantity of various enterprises, the inventory of all kinds of raw materials, the supply quantity of suppliers, the transshipment capacity and loss of transporters, and so on.After a comprehensive evaluation of enterprises, suppliers and transporters, a reasonable decision-making plan for ordering, supply and transshipment is put forward.First of all, this paper puts forward three mathematical indicators according to the supply characteristics of suppliers: supply capacity (average supply capacity), supply stability (coefficient of variation) and supply and demand satisfaction (safety factor).Secondly, based on these indicators, the supply characteristics of 402 suppliers are quantitatively analyzed.Then, in order to meet the production demand and maintain not less than the raw material inventory that meets the production demand for two weeks, we use these constraints and the consumption of three types of raw materials during production to establish a 0-1 programming model.It is concluded that at least 32 suppliers need to be selected to meet the production demand.In order to make the most economical order transfer plan, we set up an ARIMA time series model to forecast the order quantity of 32 suppliers in the next 24 weeks based on the order data of 240 weeks, and worked out the optimization scheme.It is found that in the next 24 weeks, the total ordering volume of the ordering and transshipment program will be reduced by 28.71% on average, and the ordering and transshipment costs will be reduced by 28.21% on average (see figure 5 and figure 6 of the text for details).