Efficient Green Supply Chain Management for Transit Manufacturing Enterprises Integrating AHP, K-NN, and MILP in the Context of Sustainable Development

Abstract

At present, most research on supply chain network design only considers the horizontal game of commodity greenness of the supply chain, and does not consider the vertical cooperative mode, and does not consider the impact of their own economic development on the environment. Therefore, the green supply chain network of transshipment manufacturing enterprises is designed. Firstly, the index of green supply chain is optimized and a more comprehensive index system is developed. Then, the K-nearest neighbor and decision tree algorithms are used to pre-process the partner data, and the partner is double-screened according to the index. To solve the large error in judging a single weight factor, the compound weight method is used to integrate the weight factors in two dimensions. Finally, the branch-and-bound algorithm mixed integer linear programming is used to solve the quantity of goods transported by the partners and the specific distribution route. Through the experimental analysis, compared with the traditional supply chain model, the supply chain network designed by the research reduces the cost expenditure by 34.26%, the pollution by 30.25%, the transportation loss by 37.12%, the transportation distance by 42.45%, and the transportation time by 28.47. It can effectively realize the sustainable development of enterprises and reduce the pollution generated by enterprises. INDEX TERMS Green supply chain, K-nearest neighbor algorithm, Composite weight method, Sustainable development