Bi-goal evolution for many-objective optimization problems
- Submitting institution
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The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 91072922
- Type
- D - Journal article
- DOI
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10.1016/j.artint.2015.06.007
- Title of journal
- Artificial Intelligence
- Article number
- -
- First page
- 45
- Volume
- 228
- Issue
- -
- ISSN
- 0004-3702
- Open access status
- Out of scope for open access requirements
- Month of publication
- July
- Year of publication
- 2015
- 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
- 97
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The optimisation process of real-world problems can be a demanding task,
particularly with modern requirements, where more and more competing
objectives/criteria need to be considered simultaneously. This work focused
on solving such many-objective optimisation scenarios. It converted a
many-objective problem into a bi-goal problem regarding convergence and
diversity, creating a meta-optimisation problem in which the objectives are
the goals of the search process itself.
The paper is the first paper published in the AI flagship journal Artificial
Intelligence on designing a many-objective optimiser. From its appearance to
today, it is the most cited paper (1st of 409) in that journal.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -