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

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

1
College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2
School of Economics and Management, Southeast University, Nanjing 211189, China
*
Author to whom correspondence should be addressed.
Received: 22 January 2018 / Revised: 27 February 2018 / Accepted: 27 February 2018 / Published: 3 March 2018
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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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. View Full-Text
Keywords: grey multi-source heterogeneous data; kernel and greyness degree; multi-attribute decision making; green supplier selection grey multi-source heterogeneous data; kernel and greyness degree; multi-attribute decision making; green supplier selection
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Sun, H.; Dang, Y.; Mao, W. A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection. Int. J. Environ. Res. Public Health 2018, 15, 446.

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