A case study of algorithm selection for the traveling thief problem
- authored by
- Markus Wagner, Marius Lindauer, Mustafa Mısır, Samadhi Nallaperuma, Frank Hutter
- Abstract
Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013 as the combination of two well-understood combinatorial optimization problems. With this article, we contribute in four ways. First, we create a comprehensive dataset that comprises the performance data of 21 TTP algorithms on the full original set of 9720 TTP instances. Second, we define 55 characteristics for all TPP instances that can be used to select the best algorithm on a per-instance basis. Third, we use these algorithms and features to construct the first algorithm portfolios for TTP, clearly outperforming the single best algorithm. Finally, we study which algorithms contribute most to this portfolio.
- External Organisation(s)
-
University of Adelaide
University of Freiburg
Nanjing University of Aeronautics and Astronautics
The University of Sheffield
- Type
- Article
- Journal
- Journal of heuristics
- Volume
- 24
- Pages
- 295-320
- No. of pages
- 26
- ISSN
- 1381-1231
- Publication date
- 06.2018
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Software, Information Systems, Computer Networks and Communications, Control and Optimization, Management Science and Operations Research, Artificial Intelligence
- Electronic version(s)
-
https://arxiv.org/abs/1609.00462 (Access:
Open)
https://doi.org/10.1007/s10732-017-9328-y (Access: Closed)