Abstract
The Algorithm Selection Problem seeks to select the most suitable algorithm for a given problem. For solving it, the algorithm selection systems have to face the so-called cold start. It concerns the disadvantage that arises in those cases where the system involved in the selection of the algorithm has not enough information to give an appropriate recommendation. Bearing that in mind, the main goal of this work is two-fold. On the one hand, a novel meta-learning-based approach that allows selecting a suitable algorithm for solving a given logistic problem is proposed. On the other hand, the proposed approach is enabled to work within cold start situations where a tree-structured hierarchy that enables to compare different metric dataset to identify a particular problem or variation is presented.
Original language | English |
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Title of host publication | Computer Aided Systems Theory – EUROCAST 2017 |
Subtitle of host publication | 16th International Conference, Las Palmas de Gran Canaria, Spain, February 19-24, 2017. Revised Selected Papers, Part I |
Editors | Roberto Moreno-Díaz, Franz Pichler, Alexis Quesada-Arencibia |
Place of Publication | Cham |
Publisher | Springer |
Pages | 339-346 |
Number of pages | 8 |
ISBN (Electronic) | 978-3-319-74718-7 |
ISBN (Print) | 978-3-319-74717-0 |
DOIs | |
Publication status | Published - 1 Jan 2018 |
Event | 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 - Las Palmas de Gran Canaria, Spain Duration: 19 Feb 2017 → 24 Feb 2017 Conference number: 16 http://eurocast2017.fulp.ulpgc.es/ |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10671 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 |
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Abbreviated title | EUROCAST 2017 |
Country | Spain |
City | Las Palmas de Gran Canaria |
Period | 19/02/17 → 24/02/17 |
Internet address |
Keywords
- Logistic problems
- Meta-heuristics
- Meta-learning