A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. (December 2019)

• Record Type: Journal Article
• Authors: Zhang, Hao; Cui, Yan
• Is Part Of: Simulation. Volume 95:Number 12(2019)
• Page Start: 1165
• Page End: 1183
• Publication Date: 2019-12
• Subjects: Agricultural means of production -- Bayesian network -- genetic algorithm -- green supplier selection; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549719826306
• Languages: English
• ISSNs: 0037-5497

Abstract

With the advancement of agricultural modernization, many suppliers of agricultural means of production have delivery delay problems and have created environmental pollution and other issues, which affect the coordination and overall efficiency of the agricultural supply chain. Focusing on the green suppliers, this paper puts forward a series of evaluation indexes and considers the influence of environmental performance for performing uncertainty event reasoning based on a Bayesian network – establishing a complete selection and evaluation system for retail enterprises and downstream customers. In addition, an improved genetic algorithm is combined with the Bayesian approach to quantify the evaluation indicators, which solves the problems of the traditional methods of information occlusion and an unreasonable selection scheme, and provides an intelligent and efficient selection of green suppliers.