Nonadditivity index and capacity identification method in the context of multicriteria decision making

被引:44
作者
Wu, Jian-Zhang [1 ]
Beliakov, Gleb [2 ,3 ]
机构
[1] Ningbo Univ, Sch Business, Ningbo 315211, Zhejiang, Peoples R China
[2] Deakin Univ, Sch Informat Technol, Melbourne, Vic 3125, Australia
[3] RUDN Univ, Peoples Friendship Univ Russia, 6 Miklukho Maklaya St, Moscow 117198, Russia
基金
中国国家自然科学基金;
关键词
Multicriteria decision making (MCDM); Fuzzy measure; Capacity identification; Nonadditivity; Interaction index; FUZZY MEASURES; REPRESENTATIONS;
D O I
10.1016/j.ins.2018.08.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Nonadditivity is an essential property of the capacities defined on the sets of decision criteria. Nonadditivity extends the additivity of traditional probability measures and enables capacities to flexibly represent the interaction phenomenon between the decision criteria. We propose the nonadditivity index to quantify the degree and kind of nonadditivity of a capacity, discuss some properties of this index, and present some tools to help decision makers determine the nonadditivity index of given subset. The nonadditivity index based capacity identification method is proposed and formulated in terms of linear constraints representing the decision makers' explicit or implicit preferences. A linear programming model is formulated as an aid for an optimal capacity identification. The proposed capacity identification method is illustrated on an example. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:398 / 406
页数:9
相关论文
共 35 条
[1]
[Anonymous], 2014, DATA MINING APPL R
[2]
[Anonymous], 1974, Theory of Fuzzy Integrals and Applications
[3]
Fuzzy implications based on semicopulas [J].
Baczynski, Michal ;
Grzegorzewski, Przemyslaw ;
Mesiar, Radko ;
Helbin, Piotr ;
Niemyska, Wanda .
FUZZY SETS AND SYSTEMS, 2017, 323 :138-151
[4]
Banzhaf J.F., 1965, Rutgers Law Review, V19, P317
[5]
Using the Choquet Integral in the Fuzzy Reasoning Method of Fuzzy Rule-Based Classification Systems [J].
Barrenechea, Edurne ;
Bustince, Humberto ;
Fernandez, Javier ;
Paternain, Daniel ;
Antonio Sanz, Jose .
AXIOMS, 2013, 2 (02) :208-223
[6]
Beliakov G, 2016, STUD FUZZ SOFT COMP, V329, P1, DOI 10.1007/978-3-319-24753-3
[7]
Beliakov G., 2007, AGGREGATION FUNCTION, DOI DOI 10.1007/978-3-540-73721-6
[8]
Learning Choquet-Integral-Based Metrics for Semisupervised Clustering [J].
Beliakov, Gleb ;
James, Simon ;
Li, Gang .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2011, 19 (03) :562-574
[9]
Construction of aggregation functions from data using linear programming [J].
Beliakov, Gleb .
FUZZY SETS AND SYSTEMS, 2009, 160 (01) :65-75
[10]
SOME CHARACTERIZATIONS OF LOWER PROBABILITIES AND OTHER MONOTONE CAPACITIES THROUGH THE USE OF MOBIUS-INVERSION [J].
CHATEAUNEUF, A ;
JAFFRAY, JY .
MATHEMATICAL SOCIAL SCIENCES, 1989, 17 (03) :263-283