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Pré-Publication, Document De Travail Année : 2021

Convexity conditions for normal mean-variance mixture distribution in joint probabilistic constraints

Hoang Nam Nguyen
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Abdel Lisser

Résumé

In this paper, we study the linear programming with probabilistic constraints. We suppose that the distribution of the constraint rows is a normal mean-variance mixture distribution and the dependence of rows is represented by an Archimedean copula. We prove the convexity of the feasibility set in some additional conditions. Next, we propose a sequential approximation by linearization which provides a lower bound and a gradient descent method which provides an upper bound with numerical results.
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Dates et versions

hal-03092800 , version 1 (02-01-2021)

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  • HAL Id : hal-03092800 , version 1

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Hoang Nam Nguyen, Abdel Lisser. Convexity conditions for normal mean-variance mixture distribution in joint probabilistic constraints. 2021. ⟨hal-03092800⟩
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