Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
A method based on stochastic dominance degrees for stochastic multiple criteria decision making
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea
Expert Systems with Applications: An International Journal
A method for stochastic multiple criteria decision making based on dominance degrees
Information Sciences: an International Journal
Combining prospect theory and fuzzy numbers to multi-criteria decision making
Expert Systems with Applications: An International Journal
Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method
Mathematical and Computer Modelling: An International Journal
Extension of TOPSIS for decision-making problems with interval data: Interval efficiency
Mathematical and Computer Modelling: An International Journal
Review: A state-of the-art survey of TOPSIS applications
Expert Systems with Applications: An International Journal
Extended TODIM method for hybrid multiple attribute decision making problems
Knowledge-Based Systems
A direct interval extension of TOPSIS method
Expert Systems with Applications: An International Journal
A study of TODIM in a intuitionistic fuzzy and random environment
Expert Systems with Applications: An International Journal
Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set
Expert Systems with Applications: An International Journal
Short Communication: IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making
Knowledge-Based Systems
Hi-index | 12.05 |
Due to the difficulty in some situations of expressing the ratings of alternatives as exact real numbers, many well-known methods to support Multicriteria Decision Making (MCDM) have been extended to compute with many types of information. This paper focuses on the information represented as probability distribution. Many of the methods that deal with probability distribution use the concept of stochastic dominance, which imposes very strong restrictions to differentiate two probability distributions, or uses the probability distributions to obtain a quantity that will be used to rank the alternatives. This paper brings the Hellinger distance concept to the MCDM context to assist the models to deal with probability distributions in a direct way without any transformation. Transformations in the data or summary quantities may miss represent the original information. For direct comparisons among probability distributions we use the stochastic dominance degree (SDD). We illustrate how simple it can be to adapt the existing methods to deal with probability distributions through the Hellinger distance and SDD by adapting the TOPSIS and TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) methods.