Code and Data Repository for Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs

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.

Authors

Rohit Kannan (ORCID: https://orcid.org/0000-0002-7963-7682)
Harsha Nagarajan (ORCID: https://orcid.org/0000-0003-4550-1100)
Deepjyoti Deka (ORCID: https://orcid.org/0000-0003-3928-3936)

Publication Details

Journal: INFORMS journal on computing
Published: 2025-08-04
DOI: https://doi.org/10.1287/ijoc.2023.0424.cd
Citations: 1
Primary Topic: Optimization and Packing Problems
Type: article
Field-Weighted Citation Impact: 1.24

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article

Code and Data Repository for Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs

Rohit Kannan, Harsha Nagarajan, Deepjyoti Deka

Aug 4, 2025

1 citations

INFORMS journal on computing

Optimization and Packing Problems

1.24

article

Code and Data Repository for Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs

Rohit Kannan, Harsha Nagarajan, Deepjyoti Deka

August 4, 2025article en

1 citations

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.

INFORMS journal on computing

Openalex Percentile: Top 17%

Optimization and Packing Problems

1.24

DOI Source OpenAlex

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Code and Data Repository for Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs — Rohit Kannan, Harsha Nagarajan, et al. · INFORMS journal on computing (2025) | TGRS Research Map | TGRS