Code and Data Repository for Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs | Synapse
September 10, 2025INFORMS journal on computing0 citations
This repository supports the global optimization of nonconvex QCQPs using innovative machine learning methods.
Tools in the repository aim to enhance problem-solving efficiency for complex nonconvex optimization tasks.
The dataset and software included facilitate the application of strong partitioning strategies in optimization.
Data from the research by Kannan, Nagarajan, and Deka offers a foundation for future studies on this optimization challenge.
Abstract
The software and data in this repository are a snapshot of the software and data that were used in the research reported in the paper by R. Kannan, H. Nagarajan, and D. Deka.