Exploiting aggregate sparsity in second-order cone relaxations for quadratic constrained quadratic programming problems-Reference-Cited by-同舟云学术

Exploiting aggregate sparsity in second-order cone relaxations for quadratic constrained quadratic programming problems

Published:2020-09-29 Issue: Volume: Page:1-19
ISSN:1055-6788
Container-title:Optimization Methods and Software
language:en
Short-container-title:Optimization Methods and Software

Author:

Sheen Heejune¹,Yamashita Makoto²^ORCID

Affiliation:

1. School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA

2. Department of Mathematical and Computing Science, Tokyo Institute of Technology, Tokyo, Japan

Funder

JSPS KAKENHI

Publisher

Informa UK Limited

Subject

Applied Mathematics,Control and Optimization,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/10556788.2020.1827256

Reference38 articles.

1. A.A. Ahmadi and A. Majumdar, DSOS and SDSOS optimization: LP and SOCP-based alternatives to sum of squares optimization, 48th Annual Conference on Information Sciences and Systems (CISS), IEEE, 2014, pp. 1–5.

2. A.A. Ahmadi and A. Majumdar, Software for DSOS and SDSOS optimization, 2014. Available at https://github.com/spot-toolbox/spotless (accessed on September 25th, 2019).

3. M. Alfaki, Models and solution methods for the pooling problem, PhD thesis, The University of Bergen, 2012.

4. Second-order cone programming

5. Recent advances in the solution of quadratic assignment problems

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