Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/246356 
Year of Publication: 
2018
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 5 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2018 [Pages:] 288-305
Publisher: 
Elsevier, Amsterdam
Abstract: 
The use of discretization in decision analysis allows practitioners to use only a few assessments to estimate the certain equivalent (CE) or expected value of a decision without knowing the functional form of the distribution of each uncertainty. The discretization shortcuts are fast, but are created with a specific distribution, or families of distributions in mind. The discretizations are not formulated with the decision problem in mind. Each discretization is specific to one uncertainty distribution, or is even more generalized. In this article, we introduce a novel mathematical formulation for selecting an optimal discretization for a specific problem. With optimal discretization, a decision analyst can use the newly-created shortcuts in repeated decisions and improve the expected accuracy of the CE calculations.
Subjects: 
Optimization
Discretization
Joint discretization
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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