# General Heuristics for Nonconvex Quadratically Constrained Quadratic Programming

## TL;DR

This paper presents a flexible framework and heuristics for approximately solving complex nonconvex QCQPs, along with an open-source Python package for practical implementation.

## Contribution

It introduces the Suggest-and-Improve framework that generalizes existing methods and provides new heuristics for nonconvex QCQPs.

## Key findings

- Framework effectively generalizes known methods
- Provides practical heuristics for difficult QCQPs
- Open-source Python package available for use

## Abstract

We introduce the Suggest-and-Improve framework for general nonconvex quadratically constrained quadratic programs (QCQPs). Using this framework, we generalize a number of known methods and provide heuristics to get approximate solutions to QCQPs for which no specialized methods are available. We also introduce an open-source Python package QCQP, which implements the heuristics discussed in the paper.