Matrix factorization based benchmark set analysis: A case study on HyFlex
The present paper offers an analysis strategy to examine benchmark sets of combinatorial search problems. Experimental analysis has been widely used to compare a set of algorithms on a group of instances from such problem domains. These studies mostly focus on the algorithms’ performance rather than the quality of the target benchmark set. In relation to that, the insights about the algorithms’ varying performance happen to be highly limited. The goal here is to introduce a benchmark set analysis strategy that can tell the quality of a benchmark set while allowing to retrieve some insights regarding the algorithms’ performance. A matrix factorization based strategy is utilized for this purpose. A Hyper-heuristic framework, i.e. HyFlex, involving 6 problem domains is accommodated as the testbed to perform the analysis on.
Duke Scholars
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- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Start / End Page
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences