A case study of algorithm selection for the traveling thief problem

Markus Wagner, Marius Lindauer, Mustafa Mısır, Samadhi Nallaperuma, Frank Hutter

Research output: Contribution to journalArticleResearchpeer-review

37 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)295-320
Number of pages26
JournalJournal of Heuristics
Volume24
Issue number3
DOIs
Publication statusPublished - Jun 2018
Externally publishedYes

Keywords

  • Algorithm portfolio
  • Combinatorial optimization
  • Instance analysis

Cite this