A multigrid approach to SDP relaxations of sparse polynomial optimization problems
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2147
- Type
- D - Journal article
- DOI
-
10.1137/16M1109060
- Title of journal
- SIAM Journal on Optimization
- Article number
- -
- First page
- 1
- Volume
- 28
- Issue
- 1
- ISSN
- 1052-6234
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
10.1137/16M1109060
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A high-impact application of large-scale semidefinite programming (SDP) is the computation of stable solutions to optimal control problems. However, solving the large-scale SDPs that appear in stability calculations of many practical optimal control problems is impossible. Fortunately, many applications have the same structures as the ones exploited in this paper. The work was presented in invited sessions at ICCOPT'16 (Tokyo) and SIOPT'17 (Vancouver). It led to an award of an Industrial CASE Ph.D. Studentship to investigate the application of this methodology to the design and manufacture of small nuclear reactors in collaboration with Civil Engineering and Rolls Royce.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
