| Affiliation: | 1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China;2. College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310023, China;3. Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS 39762, USA;4. Hangzhou Hangyang Turbomachinery Co., Ltd, Hangzhou 311300, China;5. Mechanical Light Industry Inspection Department, Zhejiang Fangyuan Test Group Co., Ltd, Hangzhou 311300, China;1. Department of Construction Management, Louisiana State University, Baton Rouge 70803, USA;2. Department of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge 70803, USA;1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China;2. College of Mechanical Engineering, Chongqing University, Chongqing 400044, China;3. School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China;1. College of Engineering, China Agricultural University, No.17 Tsinghua East Road, Haidian District, Beijing 100083, China;2. Key Laboratory of Optimal Design of Modern Agricultural Equipment, College of Engineering, China Agricultural University, No.17 Tsinghua East Road, Haidian District, Beijing 100083, China;1. School of Management, Harbin Institute of Technology, Harbin 150001, China;2. School of Architecture, Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong 518055, China;3. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin, China |
| Abstract: | Quantifying the uncertain linguistic evaluation from decision-makers (DMs) is one of the most challenging parts in the conceptual design decision. Although fuzzy decision models have been widely used to capture potential uncertainty by assigning a fuzzy term with the certain belief, the ambiguity subjective evaluation of semantic variables with conflict beliefs derived from DMs have not been well addressed. To solve this drawback, a concept decision model based on Dempster-Shafer (DS) evidence theory and intuitionistic fuzzy -Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) considering the ambiguity semantic variables fusion is proposed. Firstly, by incorporating semantic variables of intuitionistic fuzzy sets (IFSs), the diversified semantic judgments and its belief will be taken into account to form an ambiguity semantic initial decision matrix; secondly, the DS combination rule will be used to fuse the different semantic variables of multi-DMs in each scheme, update the belief of each semantic variable, and then the semantic fusion value matrix of the scheme will be constructed; finally, the weight of each evaluation objective will be calculated based on the value matrix and information entropy model, IFS-VIKOR model will be constructed to rank the concepts. A case study of the tree climbing and trimming machine will be employed to verify the proposed decision model. This decision model considering diversifying semantic variables and the conflict belief is proven to be effective compared with the IFS-SAW and ISF-TOPSIS. |
