Trust-based consensus reaching process for product design decision-making with heterogeneous information

Pursuing a consensual result is vital for selecting optimum product design schemes as it helps eliminate preference conflicts in product design decision-making (PDDM). As a dynamic and iterative activity, the consensus reaching process (CRP) of PDDM always involves heterogeneous, vague, and inconsistent information, which makes it challenging to adjust decision-makers’ judgement to achieve an acceptable consensus level. To address this issue, triangular fuzzy numbers were introduced to depict decision-makers’ heterogeneous judgement. The indicator weights were determined by integrating the fixed weight obtained from the interval analytic hierarchy process (IAHP) and the variable weight acquired using the maximizing deviation method. Decision-makers’ weights were identified through a combination of the uncertainty degree measured by fuzzy entropy and the consistency degree solved by a distance minimizing model of the PDDM matrix. A dynamic CRP for PDDM was proposed by adjusting decision-makers’ judgement based on their trust relationships and updating the PDDM matrix in an evolutionary manner. A case study is conducted to verify the feasibility and effectiveness of the proposed method.