A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem
Data Structures and Algorithms
2012-08-14 v1
Abstract
Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesman problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.
Cite
@article{arxiv.1208.2318,
title = {A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem},
author = {Olaf Mersmann and Bernd Bischl and Heike Trautmann and Markus Wagner and Frank Neumann},
journal= {arXiv preprint arXiv:1208.2318},
year = {2012}
}
Comments
33 pages, 17 figure