An integrated Shannon entropy and TOPSIS for product design concept evaluation based on bijective soft set

Abstract

This work addresses the problem of concept evaluation in uncertain environments of early design stages, with the help of the proposed integrated method involving bijective soft sets, Shannon entropy and technique for order of preference by similarity to ideal solution (TOPSIS). The application of soft set theory in the domain of product design and development is still not being efficiently utilised by previous works. Therefore, the benefit of soft set theory to define the attributes of an object through any type of approximations is used to deal with qualitative description of design criteria, by designers, and the linguistic requirements of customers. Bijective soft sets help the designers to effectively map individual customer requirements to the generated design concepts. With the help of Shannon entropy, customers’ preferences among the identified needs are captured in the new product development process, thus, improving the overall effectiveness of the concept evaluation process. This work considers concept evaluation process as a group multiple criteria decision making problem where, design specifications and customer requirements in qualitative form are first captured by using soft set theory and Shannon entropy and then, this information is incorporated in the framework of TOPSIS to identify the best concept in the evaluation process. The developed integrated method for concept evaluation process is validated with the help of a design illustration, which shows that soft set theory can serve as an effective tool for designers and researchers to reduce the imprecise and vague content of early design stages.