Disciplined Quasiconvex Programming
Abstract
We present a composition rule involving quasiconvex functions that generalizes the classical composition rule for convex functions. This rule complements well-known rules for the curvature of quasiconvex functions under increasing functions and pointwise maximums. We refer to the class of optimization problems generated by these rules, along with a base set of quasiconvex and quasiconcave functions, as disciplined quasiconvex programs. Disciplined quasiconvex programming generalizes disciplined convex programming, the class of optimization problems targeted by most modern domain-specific languages for convex optimization. We describe an implementation of disciplined quasiconvex programming that makes it possible to specify and solve quasiconvex programs in CVXPY 1.0.
Keywords
Cite
@article{arxiv.1905.00562,
title = {Disciplined Quasiconvex Programming},
author = {Akshay Agrawal and Stephen Boyd},
journal= {arXiv preprint arXiv:1905.00562},
year = {2020}
}
Comments
p. 4: corrected typos