Stochastic dominance and expected utility: survey and analysis
Management Science
Multi-criteria analysis in the evaluation of advanced manufacturing technology using PROMETHEE
Proceedings of the 14th annual conference on Computers and industrial engineering
Decision making for facility layout problem solutions
Computers and Industrial Engineering
An integrated fuzzy multi-criteria decision making method for manufacturing strategies
Computers and Industrial Engineering
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Modelling a nationwide crop planning problem using a multiple criteria decision making tool
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
Efficient Diversification According to Stochastic Dominance Criteria
Management Science
Fuzzy decision making of profit function in production planning using S-curve membership function
Computers and Industrial Engineering
A fuzzy group decision making approach for bridge risk assessment
Computers and Industrial Engineering
Computers and Industrial Engineering
A method for stochastic multiple criteria decision making based on dominance degrees
Information Sciences: an International Journal
Computers and Industrial Engineering
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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In this paper, a novel method based on the stochastic dominance degree (SDD) is proposed to solve a discrete stochastic multiple criteria decision-making (MCDM) problem. Firstly, a concept of stochastic dominance degree is introduced to describe the degree that one alternative dominates another when the SD relation for each pair of alternatives is determined, and a computation formula of the SDD is given. Then, by calculating SDDs, the SDD matrix on pairwise comparisons of alternatives with respect to each criterion is built. Furthermore, the SDD matrices with respect to all the criteria are aggregated into an overall SDD matrix using the simple additive weighting method. Based on the overall SDD matrix, an approach based on the idea of the PROMETHEE-II is developed to obtain the ranking result of alternatives. Finally, two numerical examples are used to illustrate the applicability and effectiveness of the proposed method.