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Stochastic multiple‐criteria decision making with 2‐tuple aspirations: a method based on disappointment stochastic dominance
Author(s) -
Liang Xia,
Jiang Yanping,
Liu Peide
Publication year - 2018
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12430
Subject(s) - disappointment , stochastic dominance , dominance (genetics) , mathematics , stochastic process , mathematical economics , ranking (information retrieval) , electre , computer science , econometrics , mathematical optimization , statistics , multiple criteria decision analysis , psychology , artificial intelligence , social psychology , biochemistry , chemistry , gene
Considering the disappointment aversion behavior of decision makers, we define three types of disappointment stochastic dominance rules and disappointment stochastic dominance degree between two stochastic variables. Then we prove some important properties of disappointment stochastic dominance. With respect to the stochastic multiple‐criteria decision‐making (SMCDM) problem with criterion 2‐tuple aspirations, a novel method based on disappointment stochastic dominance is proposed. To begin with, based on the 2‐tuple aspiration on each criterion, for the situations of discrete and continuous stochastic criterion values, the aspiration alternative and its cumulative distribution functions of stochastic criterion values are constructed. Next, the disappointment stochastic dominance relation between each alternative and aspiration alternative is determined based on the definition of disappointment stochastic dominance. Further, the corresponding disappointment stochastic dominance degree is calculated. And the overall disappointment stochastic dominance degree of each alternative over the aspiration alternative is calculated to obtain the ranking result. Finally, an example of selecting desirable computer development project(s) is given to illustrate the feasibility and validity of the proposed method.