MOEA/D with adaptive weight adjustment
- Submitting institution
-
Abertay University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 24145922
- Type
- D - Journal article
- DOI
-
10.1162/EVCO_a_00109
- Title of journal
- Evolutionary Computation
- Article number
- -
- First page
- 231
- Volume
- 22
- Issue
- 2
- ISSN
- 1063-6560
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- 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
-
5
- Research group(s)
-
D - Modelling & Simulation
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This 2014 paper presents an improvement to the established MOEA/D algorithm in order to overcome the key limitation of that algorithm, i.e. dealing with complex Pareto fronts, through an adaptive weight adjustment strategy. MOEA/AWA is still (in 2021) cited as a promising evolutionary algorithm in the field of MOEA. MOEA/AWA continues to be used as a benchmark for algorithm performance in recent (2020) original research papers.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
