文献类型：期刊文献

英文题名：On prioritized weighted aggregation in multi-criteria decision making

作者：Yan, Hong-Bin[1];Huynh, Van-Nam[2];Nakamori, Yoshiteru[2];Murai, Tetsuya[3]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Japan Adv Inst Sci & Technol, Sch Knowledge Sci, Nomi, Ishikawa 9231292, Japan;[3]Hokkaido Univ, Grad Sch Informat Sci & Technol, Kita Ku, Sapporo, Hokkaido 0600814, Japan

年份：2011

卷号：38

期号：1

起止页码：812

外文期刊名：EXPERT SYSTEMS WITH APPLICATIONS

收录：;EI(收录号：20103813240968);WOS:【SSCI(收录号:WOS:000282607800091)，SCI-EXPANDED(收录号:WOS:000282607800091)】；

语种：英文

外文关键词：Multi-criteria decision making (MCDM); Prioritized aggregation; Ordered weighted averaging (OWA); Triangular norms (t-norms); Benchmark; Lukasiewicz implication; Fuzzy target-oriented decision analysis

摘要：This paper deals with multi-criteria decision making (MCDM) problems with multiple priorities, in which priority weights associated with the lower priority criteria are related to the satisfactions of the higher priority criteria. Firstly, we propose a prioritized weighted aggregation operator based on ordered weighted averaging (OWA) operator and triangular norms (t-norms). To preserve the tradeoffs among the criteria in the same priority level, we suggest that the degree of satisfaction regarding each priority level is viewed as a pseudo criterion. On the other hand. t-norms are used to model the priority relationships between the criteria in different priority levels. In particular, we show that strict Archimedean t-norms perform better in inducing priority weights. As Hamacher family of t-norms provide a wide class of strict Archimedean t-norms ranging from the product to weakest t-norm, Hamacher parameterized t-norms are used to induce the priority weight for each priority level. Secondly, considering decision maker (DM)'s requirement toward higher priority levels, a benchmark based approach is proposed to induce priority weight for each priority level. In particular, Lukasiewicz implication is used to compute benchmark achievement for crisp requirements; target-oriented decision analysis is utilized to obtain the benchmark achievement for fuzzy requirements. Finally, some numerical examples are used to illustrate the proposed prioritized aggregation technique as well as to compare with previous research. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.