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Article type: Research Article
Authors: Hu, Haiyana; * | Ren, Zhiqiangb
Affiliations: [a] School of Civil Engineering and Transportation Engineering, Yellow River Conservancy Technical Institute, Kaifeng, Henan, China | [b] Anyang Natural Resources and Planning Bureau, Anyang, Henan, China
Correspondence: [*] Corresponding author: Haiyan Hu, School of Civil Engineering and Transportation Engineering, Yellow River Conservancy Technical Institute, Kaifeng, Henan 475004, China. E-mail: hushoubuliao@163.com.
Abstract: In engineering construction, the unavoidable issue is how to choose suitable suppliers. The quality of suppliers has a direct impact on the progress, quality, and cost of the project. The selection of suppliers for construction projects in water conservancy and hydropower engineering is directly related to the cost of construction enterprises, and large-scale construction projects have stricter requirements for cost control. The investment in engineering construction is very huge, so cost control ability is a very important assessment indicator for construction project construction, and the cost of materials is a significant part of the construction project cost. Therefore, the research on the selection and optimization of building material suppliers is a topic that cannot be ignored. The building material supplier selection is a multi-attribute decision making (MADM). In this paper, some calculating laws on IVIFSs, Hamacher sum, Hamacher product are introduced, and the induced interval-valued intuitionistic fuzzy Hamacher interactive ordered weighted averaging (IVIFHIOWA) operators (I-IVIFHIOWA) operator is proposed. Meanwhile, some ideal properties of I-IVIFHIOWA operator are studied. Then, the I-IVIFHIOWA operator is employed to cope with the MADM under IVIFSs. Finally, an example for building material supplier selection is employed to test the I-IVIFHIOWA operator.
Keywords: Multi-attribute decision making (MADM), interval-valued intuitionistic fuzzy sets (IVIFSs), I-IVIFHIOWA operator, building material supplier selection
DOI: 10.3233/KES-221505
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 27, no. 4, pp. 489-502, 2023
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