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Matrix factorization based benchmark set analysis: A case study on HyFlex

Publication ,  Conference
Mısır, M
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2017

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

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319687582

Publication Date

January 1, 2017

Volume

10593 LNCS

Start / End Page

184 / 195

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Mısır, M. (2017). Matrix factorization based benchmark set analysis: A case study on HyFlex. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10593 LNCS, pp. 184–195). https://doi.org/10.1007/978-3-319-68759-9_16
Mısır, M. “Matrix factorization based benchmark set analysis: A case study on HyFlex.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10593 LNCS:184–95, 2017. https://doi.org/10.1007/978-3-319-68759-9_16.
Mısır M. Matrix factorization based benchmark set analysis: A case study on HyFlex. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 184–95.
Mısır, M. “Matrix factorization based benchmark set analysis: A case study on HyFlex.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10593 LNCS, 2017, pp. 184–95. Scopus, doi:10.1007/978-3-319-68759-9_16.
Mısır M. Matrix factorization based benchmark set analysis: A case study on HyFlex. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 184–195.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319687582

Publication Date

January 1, 2017

Volume

10593 LNCS

Start / End Page

184 / 195

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences