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This standard approach of disease modelling under uncertainty calls for a set of sensitivity analyses which are presented in section Sensitivity analyses.
+Ambiguity (Knightian Uncertainty), +Backward stochastic differential equations, nonlinear expectation, and path-dependent PDEs, +Dynamic risk measures, +Mathematical modelling under uncertainty, +Quantitative risks, +Recursive Utility, +Uncertainty quantification, +Computational aspects and numerical methods pertinent to the above topics, +Related topics, among them also relevant to statistics.
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Here, we give a review of production distribution problem modeling, optimization under uncertainty and Bi-level programming.
We consider a one-period model under uncertainty.
More precisely, it focuses on the parametric study of engineering models under uncertainty.
Numerous researchers, such as Federgruen and Heching (1999), presented a combined pricing and inventory control model under uncertainty.
This is a one period model under uncertainty that borrows features from Ehrlich (1973) and Lochner and Moretti (2001).
This research proposes a multi-period, multi-product, multi-echelon closed-loop supply chain network design model under uncertainty.
Thus, the finally obtained linear model under uncertainty can be further converted to deterministic linear models, which can be solved by conventional algorithms.
A comparative study between the proposed hybrid solution approach and other solution approaches used to solve multi-objective models under uncertainty.
These include A comparative study between the proposed hybrid solution approach and other solution approaches used to solve multi-objective models under uncertainty.
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