Uncertain random programming models in the framework of U-S chance theory and their applications
Feng Hu (),
Ziyi Qu () and
Deguo Yang ()
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Feng Hu: Qufu Normal University
Ziyi Qu: The Fourth Military Medical University
Deguo Yang: Qufu Normal University
TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2025, vol. 33, issue 1, No 7, 194 pages
Abstract:
Abstract In order to handle some problems in which human uncertainties coexist with stochasticities characterized by non-additive probabilities, we develop uncertain random programming models based on four different types of expectations in the framework of U-S chance theory. In this paper, firstly, the operational law for uncertain random variables is proved in this framework. Then, based on sub-linear expectations and Choquet integrals, four types of expectations of uncertain random variables are defined. Finally, four uncertain random programming models are proposed and applied to optimal investment in incomplete financial market and system reliability design.
Keywords: Uncertain random programming; Optimal investment; System reliability; U-S chance theory (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11750-024-00682-y
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