Affiliations: [a] School of Mathematics and Information Sciences, Guangzhou University, Guangzhou, China
| [b] Department of Mathematics, Islamabad Model College for Girls, Islamabad, Pakistan
| [c] BORDA Research Unit and Multidisciplinary Institute of Enterprise (IME), University of Salamanca, Salamanca, Spain
| [d] School of Mathematics and Information Sciences, Guangzhou University, Guangzhou, China; Guangzhou Vocational College of Science and Technology, Guangzhou, Guangdong, China
| [e] School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, PR China; Department of Mathematics, Mirpur University of Science and Technology, Mirpur (AJK), Pakistan
Correspondence:
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Corresponding author. Khizar Hayat, School of Mathematics and Information Sciences, Guangzhou University, 510000 Guangzhou, China. Tel.: +86 18344322394, +92 5647836; E-mails: khizar233@gmail.com, khizar233@e.gzhu.edu.cn and Muhammad Irfan Ali, Department of Mathematics, Islamabad Model College for Girls, F-6/2, Islamabad, Pakistan. Tel.: +92 5008784; E-mail: mirfanali@yahoo.com.
Abstract: Concept selection is among the most crucial activities in new product development, since the consequences of a bad choice may be disastrous. The recent research of concept selection benefited from soft set theory as an effective tool for that purpose. However, some uncertainties still affix in design concept evaluation, which can be overcome by utilizing membership and non-membership functions on design attributes. In this paper, a novel approach of design concept evaluation is introduced based on generalized intuitionistic fuzzy soft sets. By combining bijective soft set and intuitionistic fuzzy set, design concepts are specified on design attributes. Generalized b-intuitionistic fuzzy soft sets are used to illustrate the mapping between customer demands and generated design concepts. An algorithm is proposed to select an appropriate object from a set of objects for one or more than one customers. Finally, we present a comparison of our methodology with focal existing methods, and we identify some of their limitations.
