文献类型：期刊文献

英文题名：Linguistic multi-attribute decision making with multiple priorities

作者：Yan, Hong-Bin[1];Zhang, Xueqing[2];Li, Yashuai[3]

机构：[1]East China Univ Sci & Technol, Sch Business, Meilong Rd 130, Shanghai 200237, Peoples R China;[2]Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China;[3]Beihang Univ, Sch Econ & Management, Xueyuan Rd 37, Beijing 100191, Peoples R China

年份：2017

卷号：109

起止页码：15

外文期刊名：COMPUTERS & INDUSTRIAL ENGINEERING

收录：;EI(收录号：20171803634831);WOS:【SCI-EXPANDED(收录号:WOS:000405052300002)】；

基金：We would like to appreciate constructive comments and valuable suggestions from the three anonymous referees, which have helped us efficiently, improve the quality of this paper. This study was partly supported by the National Natural Science Foundation of China (NSFC) under grant nos. 71471063, 71502008, 71472052 and 71501006; supported by the Fundamental Research Funds for the Central Universities in China; and supported by the Social Science Funds of Beijing under grant no. 16GLC047.

语种：英文

外文关键词：Linguistic MADM; Priority hierarchy; Prioritized aggregation; 2-tuple linguistic model; Interval-valued linguistic 2-tuples

摘要：Linguistic multi-attribute decision making (MADM) problems have received many attentions in theoretical and practical aspects. It is well known that center of the linguistic MADM is the aggregation of fuzzy linguistic information. As one widely used type of aggregation operators, the importance weighted aggregation assumes that all the attributes are at the same priority level. This paper deals with linguistic MADM with multiple priorities in terms of strict priority hierarchy or weak priority hierarchy. To do so, based on the 2-tuple linguistic model and the revised product t-norm, a prioritized linguistic idempotent scoring (PLIS) operator is first proposed for linguistic MADM with a strict priority hierarchy to guarantee the idempotent property of prioritized aggregation. Moreover, as an extension of the PLIS operator, a PLIS ordered weighted averaging (PLIS-OWA) operator is proposed to solve linguistic MADM with a weak priority hierarchy. In addition, in practice decision-makers (DMs) are often unsure of their evaluations due to time pressure, lack of experience and data, and therefore may provide uncertain linguistic assessments. The PLIS and PLIS-OWA operators are also extended to the cases of prioritized MADM with interval-valued linguistic 2-tuples. Finally, three illustrative examples and comparative analysis are provided to show the effectiveness and efficiency of the proposed aggregation operators. The proposed operators outperform existing studies in terms of the idempotent property, no information loss, and heterogeneous information. (C) 2017 Elsevier Ltd. All rights reserved.