On safe tractable approximations of chance constraints

On safe tractable approximations of chance constraints

0.00 Avg rating0 Votes
Article ID: iaor20122391
Volume: 219
Issue: 3
Start Page Number: 707
End Page Number: 718
Publication Date: Jun 2012
Journal: European Journal of Operational Research
Authors:
Keywords: programming: convex
Abstract:

A natural way to handle optimization problem with data affected by stochastic uncertainty is to pass to a chance constrained version of the problem, where candidate solutions should satisfy the randomly perturbed constraints with probability at least 1‐ ϵ. While being attractive from modeling viewpoint, chance constrained problems ‘as they are’ are, in general, computationally intractable. In this survey paper, we overview several simulation‐based and simulation‐free computationally tractable approximations of chance constrained convex programs, primarily, those of chance constrained linear, conic quadratic and semidefinite programming.

Reviews

Required fields are marked *. Your email address will not be published.