An application-oriented view of modeling uncertainty
By H. Zimmermann. European Journal of Operational Research, 2000
424 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/20cdf3e5570b0ff52a106b57a00f294518df3432
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Management Science and Operations Research
- Zenonas Turskis
- Edmundas Kazimieras Zavadskas
- Jin Wang
- Jun Liu
- Hongwei Wang
- How-Sing Sii
- Stefan Nickel
- Partha Chakroborty
In Statistics and Probability
- Jin Wang
- Jun Liu
- Hongwei Wang
- How-Sing Sii
- Edmundas Kazimieras Zavadskas
- Partha Chakroborty
- Shinya Kikuchi
- Zenonas Turskis
Citations in the corpus
- Multiple criteria decision making (MCDM) methods in economics: an overview (2011, methodology): “These include two widely known groups of methods: AHP and fuzzy set theory methods (Zimmermann 2000).”
- Belief rule-base inference methodology using the evidential reasoning Approach-RIMER (2006, background): “, T ) in U can be one of the following types [11]:”
- A new additive ratio assessment (ARAS) method in multicriteria decision‐making (2010, methodology): “These include two widely known groups of methods, i.e. Analytic Hierarchy Methods (AHP) (Saaty 1977, 1994) and fuzzy set theory methods (Zimmermann 2000).”
- Analysis of optimal vendor-buyer integrated inventory policy involving defective items (2006, neutral): “Zimmermann [14] stated that the choice of the appropriate method of modeling uncertainty depends on context.”
- Place of possibility theory in transportation analysis (2006, background): “The general framework for analyzing uncertain situations has been established in the context of set theory, evidence theory, and measure theory (Zimmermann, 2000; Klir, 1999; Klir and Wierman, 2000; Smets, 1998).”
- A critical review on supply chain risk – Definition, measure and modeling ☆ (2015, background): “Reasons for the need to make decisions under these circumstances vary from lacking time and resources to collect, process and evaluate information to the inherent complexity of systems that forestalls predicting the consequences of a decision [32,59,84,161].”