Chance constrained nonlinear fractional programming with random benchmark
Optimization and Control
2023-12-27 v1
Abstract
This paper studies the chance constrained fractional programming with a random benchmark. We assume that the random variables on the numerator follow the Gaussian distribution, and the random variables on the denominator and the benchmark follow a joint discrete distribution. Under some mild assumptions, we derive a convex reformulation of chance constrained fractional programming. For practical use, we apply piecewise linear and tangent approximations to the quantile function. We conduct numerical experiments on a main economic application problem.
Cite
@article{arxiv.2312.15315,
title = {Chance constrained nonlinear fractional programming with random benchmark},
author = {Tian Xia and Jia Liu},
journal= {arXiv preprint arXiv:2312.15315},
year = {2023}
}