Landscape Analysis of a Class of NP-Hard Binary Packing Problems
- Submitting institution
-
University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6344
- Type
- D - Journal article
- DOI
-
10.1162/evco_a_00237
- Title of journal
- Evolutionary Computation
- Article number
- -
- First page
- 47
- Volume
- 27
- Issue
- 1
- ISSN
- 1063-6560
- Open access status
- Exception within 3 months of publication
- Month of publication
- March
- Year of publication
- 2019
- 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
-
1
- Research group(s)
-
-
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper's impact on the field is three-fold: it strengthened the existing evidence on the effectiveness of landscape analysis to characterise problem difficulty as shown in Madalina M. Drugan work and Octavio Ramos-Figueroa et al work. It informed the community on the impact of the underlying distribution of randomly drawn instances on the instance's difficulty which led to a better design of benchmark suits as shown in the work of Thomas Weise's group (http://iao.hfuu.edu.cn/research/directions/algorithm-performance-analysis). The definitions of natural regions that distinguish between open and closed plateaus have led to a follow-up publication (doi = {10.1145/3319619.3326858}). EPSRC partially funded (EP/N017846/1)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -