Z-preference-based multi-criteria decision-making for design concept evaluation highlighting customer confidence attitude

Abstract

Abstract The aim of customer-oriented design concept evaluation (CDCE) is to select the best product design solution from the perspective of customer. Traditionally, most of CDCE methods mainly focus on the customer preference judgement but ignore the confidence attitude of customer, namely, the reliability of preference. However, the customer’s uncertain attitude means he is unsure about his decision and could probably change his mind. With the help of Z-number, more complete customer preference information is recorded (Z-preference). The main contribution of this paper is to propose a new Z-preference-based multi-criteria decision-making (MCDM) for CDCE method that retains the confidence coefficient α in evaluation value (Z-CDCE-α) to highlight the role of confidence attitude for CDCE, rather than simply translating Z-preference into a regular fuzzy preference value. By integrating with multiple information such as preference value, confidence coefficient α and the importance rating of design attribute, a novel ideal solution definition (ISD) strategy is put forward. For the re-defined ideal solutions, the distances of alternative to ideal solutions are deduced to get the priority degree δ to sort alternatives. According to the proposed ISD strategy of Z-CDCE-α, the best concept is that its important attribute values are preferred by customers with higher certainty or least preferred by customers with lower certainty, and the customers’ preferences and confidence attitudes for its less important attribute values are opposite. A case study and two comparison experiments are carried out to validate the reasonability and feasibility of Z-CDCE-α for CDCE by comparing with different evaluation values, ISD rules and MCDM models.