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OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms

Publication ,  Conference
Mısır, M; Handoko, SD; Lau, HC
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2015

This paper introduces an automated approach called OSCAR that combines algorithm portfolios and online algorithm selection. The goal of algorithm portfolios is to construct a subset of algorithms with diverse problem solving capabilities. The portfolio is then used to select algorithms from for solving a particular (set of) instance(s). Traditionally, algorithm selection is usually performed in an offline manner and requires the need of domain knowledge about the target problem; while online algorithm selection techniques tend not to pay much attention to a careful construction of algorithm portfolios. By combining algorithm portfolios and online selection, our hope is to design a problem-independent hybrid strategy with diverse problem solving capability. We apply OSCAR to design a portfolio of memetic operator combinations, each including one crossover, one mutation and one local search rather than single operator selection. An empirical analysis is performed on the Quadratic Assignment and Flowshop Scheduling problems to verify the feasibility, efficacy, and robustness of our proposed approach.

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

Publication Date

January 1, 2015

Volume

8994

Start / End Page

59 / 73

Related Subject Headings

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

Citation

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Mısır, M., Handoko, S. D., & Lau, H. C. (2015). OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8994, pp. 59–73). https://doi.org/10.1007/978-3-319-19084-6_6
Mısır, M., S. D. Handoko, and H. C. Lau. “OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8994:59–73, 2015. https://doi.org/10.1007/978-3-319-19084-6_6.
Mısır M, Handoko SD, Lau HC. OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015. p. 59–73.
Mısır, M., et al. “OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8994, 2015, pp. 59–73. Scopus, doi:10.1007/978-3-319-19084-6_6.
Mısır M, Handoko SD, Lau HC. OSCAR: Online selection of algorithm portfolios with case study on memetic algorithms. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015. p. 59–73.

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

Publication Date

January 1, 2015

Volume

8994

Start / End Page

59 / 73

Related Subject Headings

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