A competitive divide-and-conquer algorithm for unconstrained large-scale black-box optimization
- Submitting institution
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The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 91625392
- Type
- D - Journal article
- DOI
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10.1145/2791291
- Title of journal
- ACM Transactions on Mathematical Software
- Article number
- 13
- First page
- -
- Volume
- 42
- Issue
- 2
- ISSN
- 0098-3500
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- 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
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3
- Research group(s)
-
-
- Citation count
- 94
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Large-scale black-box optimisation refers to optimisation problems where there are thousands of parameters (decision variables) and algebraic models of the problems are unavailable. They pose big challenges to any optimisation algorithm. This work addresses two important issues in solving large-scale black-box optimisation: 1) the identification of independent subproblems without explicitly knowing the formula of the objective function, and 2) the optimisation of the identified black-box subproblems.
The paper, published in a top algorithms journal, is now amongst the most cited papers (2/168) in that journal since its appearance (Web of Science).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -