  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.
