Fuzzy Grey Choquet Integral for Evaluation of Multicriteria Decision Making Problems With Interactive and Qualitative Indices

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 λ-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.