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)