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An interval-valued intuitionistic fuzzy principal component analysis model-based method for complex multi-attribute large-group decision-making

Author

Listed:
  • Liu, Bingsheng
  • Shen, Yinghua
  • Zhang, Wei
  • Chen, Xiaohong
  • Wang, Xueqing

Abstract

The complex multi-attribute large-group decision-making problems that are based on interval-valued intuitionistic fuzzy information have become a common topic of research in the field of decision-making. Due to the complexity of this kind of problem, alternatives are usually described by multiple attributes that exhibit a high degree of interdependence or interactivity. In addition, decision makers tend to be derived from different interest groups, which cause the assumption of independence between the decision maker preferences in the same interest group to be violated. Because traditional aggregation operators are proposed based on the independence axiom, directly applying these operators to the information aggregation process in the complex multi-attribute large-group decision-making problem is not appropriate. Although these operators can obtain the overall evaluation value of each alternative, the results may be biased. Therefore, we draw the thought from the conventional principal component analysis model and propose the interval-valued intuitionistic fuzzy principal component analysis model. Based on this new model, we provide a decision-making method for the complex multi-attribute large-group decision-making problem. First, we treat the attributes and the decision makers as interval-valued intuitionistic fuzzy variables, and we transform these two types of variables into several independent variables using the proposed principal component analysis model. We then obtain each alternative's overall evaluation value by utilizing conventional information aggregation operators. Moreover, we obtain the optimal alternative(s) based on the ranks of the alternative overall evaluation values. An illustrative example is provided to demonstrate the proposed technique and evaluate its feasibility and validity.

Suggested Citation

  • Liu, Bingsheng & Shen, Yinghua & Zhang, Wei & Chen, Xiaohong & Wang, Xueqing, 2015. "An interval-valued intuitionistic fuzzy principal component analysis model-based method for complex multi-attribute large-group decision-making," European Journal of Operational Research, Elsevier, vol. 245(1), pages 209-225.
  • Handle: RePEc:eee:ejores:v:245:y:2015:i:1:p:209-225
    DOI: 10.1016/j.ejor.2015.02.025
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    References listed on IDEAS

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    1. Peng, Yi & Kou, Gang & Wang, Guoxun & Shi, Yong, 2011. "FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms," Omega, Elsevier, vol. 39(6), pages 677-689, December.
    2. Huang, Yeu-Shiang & Chang, Wei-Chen & Li, Wei-Hao & Lin, Zu-Liang, 2013. "Aggregation of utility-based individual preferences for group decision-making," European Journal of Operational Research, Elsevier, vol. 229(2), pages 462-469.
    3. Matteo Brunelli & Michele Fedrizzi, 2015. "Axiomatic properties of inconsistency indices for pairwise comparisons," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 1-15, January.
    4. Brunelli, Matteo & Fedrizzi, Michele, 2015. "Boundary properties of the inconsistency of pairwise comparisons in group decisions," European Journal of Operational Research, Elsevier, vol. 240(3), pages 765-773.
    5. Merigó, José M. & Casanovas, Montserrat & Yang, Jian-Bo, 2014. "Group decision making with expertons and uncertain generalized probabilistic weighted aggregation operators," European Journal of Operational Research, Elsevier, vol. 235(1), pages 215-224.
    6. Altuzarra, Alfredo & Moreno-Jimenez, Jose Maria & Salvador, Manuel, 2007. "A Bayesian priorization procedure for AHP-group decision making," European Journal of Operational Research, Elsevier, vol. 182(1), pages 367-382, October.
    7. Zhu, Bin & Xu, Zeshui, 2014. "Analytic hierarchy process-hesitant group decision making," European Journal of Operational Research, Elsevier, vol. 239(3), pages 794-801.
    8. Xia, Meimei & Chen, Jian, 2015. "Multi-criteria group decision making based on bilateral agreements," European Journal of Operational Research, Elsevier, vol. 240(3), pages 756-764.
    9. Wang, Ying-Ming & Chin, Kwai-Sang, 2009. "A new data envelopment analysis method for priority determination and group decision making in the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 195(1), pages 239-250, May.
    10. Chen, Ting-Yu & Chang, Chien-Hung & Rachel Lu, Jui-fen, 2013. "The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making," European Journal of Operational Research, Elsevier, vol. 226(3), pages 615-625.
    11. Ahn, Byeong Seok, 2015. "Extreme point-based multi-attribute decision analysis with incomplete information," European Journal of Operational Research, Elsevier, vol. 240(3), pages 748-755.
    12. Federica Gioia & Carlo Lauro, 2006. "Principal component analysis on interval data," Computational Statistics, Springer, vol. 21(2), pages 343-363, June.
    13. Ondemir, Onder & Gupta, Surendra M., 2014. "A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system," European Journal of Operational Research, Elsevier, vol. 233(2), pages 408-419.
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