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arXiv · 1208.2318

A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem

Olaf Mersmann·Bernd Bischl·Heike Trautmann·Markus Wagner·Frank Neumann
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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.

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Olaf Mersmann, Bernd Bischl, Heike Trautmann, Markus Wagner, Frank Neumann. 2012-08-11. A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. https://arxiv.org/abs/1208.2318

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