A scalar projection and angle based evolutionary algorithm for many-objective optimization problems
- Submitting institution
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Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6 - 698465
- Type
- D - Journal article
- DOI
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10.1109/TCYB.2018.2819360
- Title of journal
- IEEE Transactions on Cybernetics
- Article number
- -
- First page
- 2073
- Volume
- 49
- Issue
- 6
- ISSN
- 2168-2267
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- 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
-
4
- Research group(s)
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A - Computing and Informatics Research Centre
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Proposes a new decomposition-based many-objective optimization algorithm by simultaneously using adaptive search directions and two reference points. This paper is significant because the proposed approach has been recognised by other researchers, with comments on its advantage: “angle-based approaches have shown promising for solving MaOPs, because the angle can purely reflect the diversity degree and combine with the convergence information more easily” [https://doi.org/10.1016/j.asoc.2019.105911], “for the recently emerged MaOEA/Ds, a more effective association metric, i.e., the acute angles between solutions and reference vectors, becomes a preferred choice” [https://doi.org/10.1016/j.ins.2020.03.104]. The research was collaborated with Sun Yat-sen University and South China University of Technology.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
