Interval-Valued Intuitionistic Uncertain Linguistic Multi-attribute Decision-Making Method for Plant Location Selection
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Interval-Valued Intuitionistic Uncertain Linguistic Multiattribute Decision-Making Method for Plant Location Selection with Partitioned Hamy Mean Zhengmin Liu1 • Hongxue Xu1 • Peide Liu1 • Lin Li1 • Xiaolan Zhao1
Received: 20 July 2019 / Revised: 23 August 2019 / Accepted: 29 August 2019 Taiwan Fuzzy Systems Association 2019
Abstract Plant location selection (PLS) is a typical and complex multi-attribute group decision-making (MAGDM) problem, which requires consideration of several alternatives and multiple attributes. However, existing research results on PLS lack sufficient consideration of complex relationship patterns between attributes, which often leads to inaccurate decision results. Thus, in this paper, a new MAGDM technique is proposed to solve the problem of PLS, in which complex interrelationship structures exist between multi-inputs and attribute values are represented as interval-valued intuitionistic uncertain linguistic variables (IVIULVs). First, to solve the shortcomings of the existing operations, some new operational rules are redefined for IVIULVs based on linguistic scale functions and Archimedean T-conorms and T-norms. These new rules of operation hold the closedness, and are flexible for semantic transformation processing. Then, to more accurately reflect the partition structure and the complex interrelationship pattern among multi-input arguments, we extend the traditional Hamy mean and propose the partitioned Hamy mean (PHAM), which can eliminate the impact of & Zhengmin Liu [email protected] Hongxue Xu [email protected] Peide Liu [email protected] Lin Li [email protected] Xiaolan Zhao [email protected] 1
School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
unrelated attributes on the results and meet the semantic conversion needs of different decision makers. Furthermore, we develop two new fuzzy linguistic aggregation operators: interval-valued intuitionistic uncertain linguistic PHAM (IVIULPHAM) and its weighted version (IVIULWPHAM). Finally, a novel MAGDM technique (IVIUL-MAGDM) based on the IVIULWPHAM operator is proposed to solve the problem of PLS. Several examples of PLS are also illustrated to show the validity and advantages of the IVIUL-MAGDM method by comparing with the other existing MAGDM methods. Keywords Multi-attribute group decision making Interval-valued intuitionistic uncertain linguistic variable Linguistic scale function Partitioned Hamy mean Plant location selection
1 Introduction In the current complex competitive environment, plant location selection (PLS) is an important basic work for manufacturing enterprises to maximize resource utilization and minimize product costs. A superior location can bring sustainable benefits to manufacturing enterprises. When evaluating the location of several alternative plants, many evaluation attributes should be considered, including traffic convenience, land price, access to raw materials, government support, etc. Therefore, PLS c
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