TY - JOUR
T1 - Fuzzy Grey Choquet Integral for Evaluation of Multicriteria Decision Making Problems with Interactive and Qualitative Indices
AU - Tian, Guangdong
AU - Hao, Nannan
AU - Zhou, Mengchu
AU - Pedrycz, Witold
AU - Zhang, Chaoyong
AU - Ma, Fangwu
AU - Li, Zhiwu
N1 - Funding Information:
Manuscript received January 13, 2019; accepted March 14, 2019. Date of publication April 12, 2019; date of current version February 17, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 51775238. This paper was recommended by Associate Editor C. Zhang. (Corresponding author: Mengchu Zhou.) G. Tian is with the Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan 250061, China, and also with the National Demonstration Center for Experimental Mechanical Engineering Education, Shandong University, Jinan 250061, China (e-mail: tiangd2013@163.com).
Publisher Copyright:
© 2013 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - Multicriteria decision making (MCDM) problems are often encountered in complex system design. Most of them need to be evaluated with a large number of interactive and qualitative indices, which are difficult to be addressed effectively through the existing methods. In this paper, a novel fuzzy Choquet integral-based grey comprehensive evaluation (GCE) method, called fuzzy grey Choquet integral (FGCI), is proposed to evaluate MCDM problems with many interactive and qualitative indices. In this method, expert evaluation of qualitative indices is represented through fuzzy linguistic values. Fuzzy values are defuzzified and standardized to obtain the original evaluation matrix. The original values are replaced by the correlation coefficients, which, to a certain extent, eliminate the influence of experts' subjective preference. An improved teaching-learning-based optimization algorithm is employed to identify -fuzzy-measures following the weights given by experts in order to enhance the consistency of weights. Then the correlation coefficients are aggregated through Choquet integral among λ -fuzzy-measures, which can reflect interactions among indices. In addition, according to the characteristics of λ -fuzzy-measures, the construction guidelines for a corresponding index system are given to overcome the limitations of FGCI. Finally, the performance of the proposed method is demonstrated via a practical example of green design evaluation and compared with the GCE method. The results validate its feasibility and effectiveness.
AB - Multicriteria decision making (MCDM) problems are often encountered in complex system design. Most of them need to be evaluated with a large number of interactive and qualitative indices, which are difficult to be addressed effectively through the existing methods. In this paper, a novel fuzzy Choquet integral-based grey comprehensive evaluation (GCE) method, called fuzzy grey Choquet integral (FGCI), is proposed to evaluate MCDM problems with many interactive and qualitative indices. In this method, expert evaluation of qualitative indices is represented through fuzzy linguistic values. Fuzzy values are defuzzified and standardized to obtain the original evaluation matrix. The original values are replaced by the correlation coefficients, which, to a certain extent, eliminate the influence of experts' subjective preference. An improved teaching-learning-based optimization algorithm is employed to identify -fuzzy-measures following the weights given by experts in order to enhance the consistency of weights. Then the correlation coefficients are aggregated through Choquet integral among λ -fuzzy-measures, which can reflect interactions among indices. In addition, according to the characteristics of λ -fuzzy-measures, the construction guidelines for a corresponding index system are given to overcome the limitations of FGCI. Finally, the performance of the proposed method is demonstrated via a practical example of green design evaluation and compared with the GCE method. The results validate its feasibility and effectiveness.
KW - Fuzzy Choquet integral
KW - grey comprehensive evaluation (GCE)
KW - multicriteria decision making (MCDM)
KW - teaching-learning-based optimization algorithm
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U2 - 10.1109/TSMC.2019.2906635
DO - 10.1109/TSMC.2019.2906635
M3 - Article
AN - SCOPUS:85101162987
SN - 2168-2216
VL - 51
SP - 1855
EP - 1868
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 3
M1 - 8689347
ER -