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Dynamic Stochastic Multiattribute Decision-Making That Considers Stochastic Variable Variance Characteristics under Time-Sequence Contingency Environments
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper presents a dynamic stochastic decision-making method that considers the characteristics of stochastic variable variances under time-sequence contingency environments for solving stochastic decision-making problems with information from different periods and of indeterminate attribute weights.
First, time-sequence weights are obtained using the technique for order preference by similarity to ideal solution (TOPSIS), corresponding with the idea of “stressing the present rather than the past.” After determining the time degree and fully considering the characteristics of normally distributed stochastic variable variances, the attribute weight is determined based on vertical projection distance.
Decision-making information is then assembled from two dimensions of time-sequence and attributes, based on the two categories of weighted arithmetic averaging operators of normally distributed stochastic variables, resulting in comprehensive dynamic decision-making from single solution dimensions and a priority sequence of solutions per the order relation criteria of normally distributed stochastic variables.
Finally, the validity and practicability of the methods proposed in this paper are verified using an example numerical analysis.
American Psychological Association (APA)
Yang, Zao-li& Huang, Lu-cheng. 2017. Dynamic Stochastic Multiattribute Decision-Making That Considers Stochastic Variable Variance Characteristics under Time-Sequence Contingency Environments. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1191672
Modern Language Association (MLA)
Yang, Zao-li& Huang, Lu-cheng. Dynamic Stochastic Multiattribute Decision-Making That Considers Stochastic Variable Variance Characteristics under Time-Sequence Contingency Environments. Mathematical Problems in Engineering No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1191672
American Medical Association (AMA)
Yang, Zao-li& Huang, Lu-cheng. Dynamic Stochastic Multiattribute Decision-Making That Considers Stochastic Variable Variance Characteristics under Time-Sequence Contingency Environments. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1191672
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191672