A hybrid fuzzy multiple criteria decision-making approach for comprehensive performance evaluation of tunnel boring machine disc cutter. (November 2020) - Lin, Laikuang; Xia, Yimin; Wu, Dun
Highlights: A novel fuzzy hybrid MCDM approach is developed and verificated. Both quantitative and qualitative criteria are employed in the proposed approach. FTOPSIS and fuzzy comprehensive evaluation are integrated for evaluation. Both subjective and objective weights are taken into account. A weight-determining method is presented based on FAHP, entropy and game theory. Abstract: Disc cutter performance evaluation and selection is one of the typical and challenging kinds of Multiple criteria decision-making (MCDM) problems. To improve the construction efficiency as well as decrease cost of tunnel boring machine (TBM) project, it is essential to evaluate the cutter performance according to the geology and construction demand. This paper develops a novel hybrid fuzzy MCDM approach to address this kind of MCDM problems in the fuzzy environment. To determine more justified weights for criteria with consideration of subjective and objective weights, a hybrid weight-determining method that integrates fuzzy AHP, entropy weight (EW), and game theory (GT) is presented. The fuzzy comprehensive evaluation and fuzzy TOPSIS are combined to obtain the evaluation results with consideration of both quantitative and qualitative criteria. The proposed approach is applied to a case study of disc cutter performance evaluation, and the final rankings of alternatives with the weights of the criteria are discussed. To verify the evaluated results, a comparative study is carried out with engineering practical data, the proposed approach, and some classical MCDM methods. Additionally, a sensitivity analysis is performed based on varying the criteria weights. The investigations show the proposed approach is reasonable, robust, and effective, which can be a precise decision-making aid to deal with many practical MCDM problems in a variety of engineering areas.