Multi-line distance minimization : a visualized many-objective test problem suite
- Submitting institution
-
The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 91072812
- Type
- D - Journal article
- DOI
-
10.1109/TEVC.2017.2655451
- Title of journal
- IEEE Transactions on Evolutionary Computation
- Article number
- -
- First page
- 61
- Volume
- 22
- Issue
- 1
- ISSN
- 1089-778X
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- 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)
-
-
- Citation count
- 23
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In multi-objective optimisation, when the number of objectives is larger than three, it is not possible to scatterplot the solutions and visually investigate an optimisation algorithm's behaviour. This paper addresses this issue by designing a test problem suite where the optimal solutions in 2D decision space are similar (in the sense of Euclidean geometry) to their preimages in high-dimensional objective space, thus enabling visual exploration.
The paper was published in the top evolutionary computation journal. Its preliminary version won the Best Student Paper Award at CEC'2014 (882 submissions), one of the largest conferences in the area.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
