Research on Raw Material Ordering and Transportation Process Based on TOPSIS and Neural Network

Abstract

The main purpose of this paper is to establish a reasonable model for the selection of suppliers for the purchase of raw materials and the reasonable selection of transporters for an enterprise whose main business is building decorative panels. Reasonable planning and selection of importers are carried out under many factors, such as meeting economic conditions, giving priority to production capacity, meeting inventory and weekly consumption and so on.This question first carries on the relevant cold melon according to the supply characteristics of 402 suppliers. Using the analytic hierarchy process, set a certain weight to the three quantified supply features to calculate the total score of a supplier, and sort it. Then the minimum number of suppliers is obtained by modeling, and these suppliers can meet the minimum requirements of the enterprise. And adopt 0-1 programming model and greedy algorithm to traverse each possibility, and then combined with BP neural network to predict the demand in the next 24 weeks, list the possibility of all selected suppliers to meet this number. After that, the maximum supply capacity and supply law of the supplier are analyzed to improve the production capacity. Enterprises need to increase the proportion of orders from these suppliers and correspondingly reduce the proportion of orders from unreliable suppliers in order to optimize production capacity.