Diversity Comparison of Pareto Front Approximations in Many-Objective Optimization
- Submitting institution
-
De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11140
- Type
- D - Journal article
- DOI
-
10.1109/TCYB.2014.2310651
- Title of journal
- IEEE Transactions on Cybernetics
- Article number
- -
- First page
- 2568
- Volume
- 44
- Issue
- 12
- ISSN
- 2168-2267
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- 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
-
2
- Research group(s)
-
-
- Citation count
- 79
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes a diversity comparison indicator (DCI) that can efficiently assess the diversity of Pareto front approximations for many-objective optimisation. DCI has been widely used in evolutionary multi-objective optimisation [it is classed as highly cited by Clarivate Analytics). This work, has led to several invited talks, including Workshop on Advances in Multi-objective Optimisation and its Applications, Shenzhen, China, 2018 [150+ participants].
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -