A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

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Authors Olaf Mersmann, Bernd Bischl, Heike Trautmann, M. Wagner, Jakob Bossek, Frank Neumann
Journal/Conference Name Annals of Mathematics and Artificial Intelligence
Paper Category
Paper 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 salesperson 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.
Date of publication 2012
Code Programming Language R
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