A polynomial-time algorithm for a nonconvex chance-constrained program under the normal approximation

We study a chance-constrained optimization problem where the random variable appearing in the chance constraint follows a normal distribution whose mean and variance both depend linearly on the decision variables. Such structure may arise in many applications, including the normal approximation to t...

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Veröffentlicht in:	Optimization letters Jg. 17; H. 2; S. 265 - 282
1. Verfasser:	Mildebrath, David
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2023
Schlagworte:	Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation Reverse convex programming Chance-constrained programming Polynomial-time algorithms Nonlinear optimization
ISSN:	1862-4472, 1862-4480
Online-Zugang:	Volltext
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