A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

Int J Environ Res Public Health. 2018 Mar 3;15(3):446. doi: 10.3390/ijerph15030446.

Abstract

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Keywords: green supplier selection; grey multi-source heterogeneous data; kernel and greyness degree; multi-attribute decision making.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Conservation of Natural Resources / statistics & numerical data*
  • Data Accuracy*
  • Decision Making*
  • Manufactured Materials / standards*
  • Models, Theoretical