Order Priority Determination in Supply Chain

Ensemble model for order priority in make-to-order systems under supply chain environment

“…In order to implement the proposed method, the following enterprise which takes the mechanical and electrical products as the main business is studied as our case study in make-to-enterprises in this section. The data set comes from [6]. As can be seen from Tab.1, the ensemble of surrogates is placed in the first rank, SVR and Kriging are almost in the same rank, they are placed in the second rank, RBF is placed in the fourth rank.…”

“…So a new evaluation index system is set up considering the information sharing in view of existing. According to the relevant literature [6], systematic analysis and expert interview, relevant factors affecting the evaluation index system for order priority can be roughly divided into three categories. One is order terms, mainly including delivery time, order profits and order amounts, another is the aspects of production, which is composed of production costs, products quality and production capacity, and the third is customer terms considering information sharing including customer order trend, order urgency degree, period of cooperation between clients and so on.…”

“…In such situation, the quantity of evaluation index for order priority becomes much more and the impact of relevant factors becomes more complicated. Naturally, the influence of individual factors for ranking priority appears non-linearity [6] . Hence, it is necessary to introduce advanced quantitative analysis tools for order production priority.…”

Order Priority Evaluation Based on Kriging Model Under Supply Chain Environment

“…The sales planning, production planning, purchase planning can be made in the shortest time. Thus, the supply time can be shortened maximally, the cost of the supply chain operation is minimized, and customer satisfaction is improved [22]. And the index of order urgency degree is used to measure supply chain information sharing, which is determined by marketing information, inventory and customer"s orders from downstream companies.…”

“…Moreover, the generalization ability of SVR largely depends on the selection of parameters, and it costs a lot of calculation to select parameters [21]. Tang and Cai [22] proposed a non-linear evaluation model for order priority based on radial basis function (RBF) neural network, the results showed the evaluation model grounded on RBF network improved the evaluation accuracy. The main merit of this method is that it does not need the complicated process decision making, but only depends on historical data.…”