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International Journal of Fuzzy Systems

, Volume 21, Issue 8, pp 2510–2523 | Cite as

An Extended Alternative Queuing Method with Linguistic Z-numbers and Its Application for Green Supplier Selection and Order Allocation

  • Chun-Yan Duan
  • Hu-Chen Liu
  • Li-Jun ZhangEmail author
  • Hua Shi
Article
  • 61 Downloads

Abstract

With the increased awareness of environmental issues worldwide, sustainable production and development have become very important for various industries. Through green supplier selection and order allocation (GSSOA), companies can save costs, improve their green performance and thus build competitive advantage. To select appropriate supply partners and reasonable allocate order quantity, this paper develops a new integrated GSSOA model through the combination of linguistic Z-numbers, alternative queuing method (AQM) and multi-objective line programming (MOLP) model. The principal contribution of this work lies in the following aspects: Firstly, the linguistic Z-numbers are adopted to express decision-makers’ performance evaluations of alternative suppliers comprehensively. Secondly, a step-weight assessment ratio analysis (SWARA) technique is used to calculate the weights of selection criteria. Then, an extended AQM is proposed for the ranking of the given green suppliers. Finally, a MOLP model is established to determine the optimal order quantity for the qualified green suppliers according to their priority values. An empirical example and a comparison analysis with the existing methods are presented to illustrate the rationality and efficiency of our developed GSSOA model.

Keywords

Green supplier selection Order allocation Linguistic Z-number Alternative queuing method (AQM) SWARA Multi-objective line programming 

Notes

Acknowledgements

The authors are very grateful to the respected editor and the anonymous referees for their insightful and constructive comments, which helped to improve the overall quality of the paper. This work was partially supported by the National Natural Science Foundation of China (Nos. 61773250, 71701153 and 71671125) and the Project funded by China Postdoctoral Science Foundation (No. 2019T120357).

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Copyright information

© Taiwan Fuzzy Systems Association 2019

Authors and Affiliations

  • Chun-Yan Duan
    • 1
  • Hu-Chen Liu
    • 2
  • Li-Jun Zhang
    • 3
    Email author
  • Hua Shi
    • 3
  1. 1.School of Economics and ManagementTongji UniversityShanghaiPeople’s Republic of China
  2. 2.College of Economics and ManagementChina Jiliang UniversityHangzhouPeople’s Republic of China
  3. 3.School of ManagementShanghai UniversityShanghaiPeople’s Republic of China

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