文献类型：期刊文献

英文题名：Non-additive multi-attribute fuzzy target-oriented decision analysis

作者：Yan, Hong-Bin[1];Van-Nam Huynh[2];Ma, Tieju[1];Nakamori, Yoshiteru[2]

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 City, Ishikawa 9231292, Japan

年份：2013

卷号：240

起止页码：21

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20132016343096);WOS:【SCI-EXPANDED(收录号:WOS:000320684900002)】；

基金：We would like to appreciate constructive comments and valuable suggestions from anonymous referees, which have helped us efficiently improve the quality of this paper. This study was partly supported by the National Natural Sciences Foundation of China (NSFC) under Grants #71101050 and #71125002, sponsored by Shanghai Pujiang Program, the Program for New Century Excellent Talents in University (NCET-09-0345), Fok Ying-Tong Education Foundation under Grant #131082, the Fundamental Research Funds for the Central Universities in China under Grant #WN1123002, and supported by SCOPE 102305001 of Ministry of Internal Affairs and Communications (MIC), Japan.

语种：英文

外文关键词：Multi-attribute decision analysis; Target-oriented decision; Target preference type; Fuzzy target; lambda-Measure; Choquet integral

摘要：As an emerging area considering behavioral aspects of decision making, target-oriented decision model lies in the philosophical root of bounded rationality as well as represents the S-shaped value function. This paper deals with multi-attribute decision analysis from target-oriented viewpoint. First, the basic (random) target-oriented decision model is extended to involve three types of target preferences: benefit target, cost target, and equal target. Next, since applying fuzzy set theory in decision analysis allows the decision maker to specify imprecise aspiration levels, fuzzy target-oriented decision analysis is formulated to model three typical types of fuzzy targets: fuzzy min, fuzzy max, and fuzzy equal. Also, different attitudes are used to derive target achievement functions, which can be viewed as a support for "probability as psychological distance". Furthermore, we have proved that multi-attribute target-oriented decision analysis has a similar structure with discrete fuzzy measure and Choquet integral. Hence, we propose using discrete fuzzy measure and Choquet integral to model non-additive multi-attribute target-oriented decision analysis. In particular, the lambda-measure is applied to reduce the difficulty of collecting information via a designed bisection search algorithm. Finally, a new product development example is used to illustrate the effectiveness and advantages of our model. The main advantages of our target-oriented decision model are its abilities to model the fuzzy uncertainty of targets as well as capture the non-additive behaviors among targets by means of discrete fuzzy measure and Choquet integral. (C) 2013 Elsevier Inc. All rights reserved.