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A new DEA common-weight multi-criteria decision-making approach for technology selection

Author

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  • Junfei Chu
  • Jie Wu
  • Chengbin Chu
  • Ming Liu

Abstract

This paper addresses an advanced manufacturing technology selection problem by proposing a new common-weight multi-criteria decision-making (MCDM) approach in the evaluation framework of data envelopment analysis (DEA). We improve existing technology selection models by giving a new mathematical formulation to simplify the calculation process and to ensure its use in more general situations with multiple inputs and multiple outputs. Further, an algorithm is provided to solve the proposed model based on mixed-integer linear programming and dichotomy. Compared with previous approaches for technology selection, our approach brings new contributions. First, it guarantees that only one decision-making unit (DMU) (referring to a technology) can be evaluated as efficient and selected as the best performer while maximising the minimum efficiency among all the DMUs. Second, the number of mixed-integer linear programs to solve is independent of the number of candidates. In addition, it guarantees the uniqueness of the final optimal set of common weights. Two benchmark instances are used to compare the proposed approach with existing ones. A computational experiment with randomly generated instances is further proceeded to show that the proposed approach is more suitable for situations with large datasets.

Suggested Citation

  • Junfei Chu & Jie Wu & Chengbin Chu & Ming Liu, 2020. "A new DEA common-weight multi-criteria decision-making approach for technology selection," International Journal of Production Research, Taylor & Francis Journals, vol. 58(12), pages 3686-3700, June.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3686-3700
    DOI: 10.1080/00207543.2019.1634294
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    Cited by:

    1. Felipe Barrera & Marina Segura & Concepción Maroto, 2022. "Sustainable Technology Supplier Selection in the Banking Sector," Mathematics, MDPI, vol. 10(11), pages 1-21, June.
    2. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.

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