Pareto or Non-Pareto: Bi-Criterion Evolution in Multi-Objective Optimization
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 028-118914-5305
- Type
- D - Journal article
- DOI
-
10.1109/TEVC.2015.2504730
- Title of journal
- Ieee Transactions On Evolutionary Computation
- Article number
- -
- First page
- 645
- Volume
- 20
- Issue
- 5
- ISSN
- 1089-778X
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- URL
-
http://bura.brunel.ac.uk/handle/2438/12127
- 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)
-
1 - Artificial Intelligence (AI)
- Citation count
- 92
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper is published in the top journal on Evolutionary Computation (Ranked No 1 in Computer Science: Theory and Methods JCR 2016), and addresses the challenging issue “Pareto or not Pareto” in many objective optimisation. The work has come up with a novel framework for the analysis, accompanied with rigorous and comprehensive evaluations. This has already provided a much-needed deep understanding of using Pareto or Non-Pareto evolutionary algorithms for multi-objective optimisation, judging by strong citations from other researchers.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
