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Leveraging TSP Solver Complementarity through Machine Learning
2017
Evolutionary Computation
The Travelling Salesperson Problem (TSP) is one of the best-studied NP-hard problems. Over the years, many different solution approaches and solvers have been developed. For the first time, we directly compare five state-of-the-art inexact solversnamely, LKH, EAX, restart variants of those, and MAOS-on a large set of well-known benchmark instances and demonstrate complementary performance, in that different instances may be solved most effectively by different algorithms. We leverage this
doi:10.1162/evco_a_00215
pmid:28836836
fatcat:5awgbc3sfngohgr6gq243v3vlm