@inproceedings{kotthoff_improving_2015,
  title = {Improving the {State} of the {Art} in {Inexact} {TSP} {Solving} using {Per}-{Instance} {Algorithm} {Selection}},
  abstract = {We investigate per-instance algorithm selection techniques for solving the Travelling Salesman Problem (TSP), based on the two state-of-the-art inexact TSP solvers, LKH and EAX. Our comprehensive experiments demonstrate that the solvers exhibit complementary performance across a diverse set of instances, and the potential for improving the state of the art by selecting between them is significant. Using TSP features from the literature as well as a set of novel features, we show that we can capitalise on this potential by building an efficient selector that achieves significant performance improvements in practice. Our selectors represent a significant improvement in the state-of-the-art in inexact TSP solving, and hence in the ability to find optimal solutions (without proof of optimality) for challenging TSP instances in practice.},
  booktitle = {{LION} 9},
  author = {Kotthoff, Lars and Kerschke, Pascal and Hoos, Holger and Trautmann, Heike},
  year = {2015},
  pages = {202--217}
}