An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts
- Submitting institution
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De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11273
- Type
- D - Journal article
- DOI
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10.1109/TCYB.2015.2403131
- Title of journal
- IEEE Transactions on Cybernetics
- Article number
- -
- First page
- 421
- Volume
- 46
- Issue
- 2
- ISSN
- 2168-2267
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2015
- 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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1
- Research group(s)
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-
- Citation count
- 103
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The proposed algorithm has become state-of-the-art for solving MOPs with complex Pareto fronts. This work has been widely recognised in the evolutionary multi-objective optimisation community [top 5% in terms of citations in WoS by Clarivate Analytics]. The work has led to several invited talks, e.g., at Northeastern University, China (14 April, 2016) and Central South University, China (10 April, 2018).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -