An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making

The quality function deployment (QFD) is an effective tool to translate the customer requirements (CRs) to the design requirements (DRs) of a product. The process of selecting the optimal innovative product design to maximize customer satisfaction is full of uncertainty and fuzziness regarding to the users' preferences, the relationships between CRs and DRs and the merits of product designs. This study proposes a multi-expert multi-criteria decision making method to solve the innovative product design selection problem by developing an enhanced QFD method combined with the complicated fuzzy linguistic representation model, the probabilistic linguistic term set (PLTS), and the ranking method, ORESTE. Firstly, we propose a probability aggregation method to integrate the individuals' subjective evaluations into group ones expressed as PLTSs. On this basis, we extend the QFD into the probabilistic linguistic context to get the DRs' fuzzy weights. Then, based on a new distance measure between PLTSs, a probabilistic linguistic global preference score function and three kinds of probabilistic linguistic preference intensity formulas are proposed. Furthermore, we develop a PL-ORESTE method to obtain the preference, indifference and incomparability relations between the alternatives. For the facility of application, we develop the procedure of the QFD-based PL-ORESTE method. Given that the “shared cars” is a new industry appeared in Chinese market, we finally illustrate the applicability of the proposed method by a case study concerning the selection of innovative designs of Panda shared cars.