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Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference

  • Jakob Bossek
  • Heike Trautmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10037)

Abstract

State of the Art inexact solvers of the NP-hard Traveling Salesperson Problem (TSP) are known to mostly yield high-quality solutions in reasonable computation times. With the purpose of understanding different levels of instance difficulties, instances for the current State of the Art heuristic TSP solvers LKH+restart and EAX+restart are presented which are evolved using a sophisticated evolutionary algorithm. More specifically, the performance differences of the respective solvers are maximized resulting in instances which are easier to solve for one solver and much more difficult for the other. Focusing on both optimization directions, instance features are identified which characterize both types of instances and increase the understanding of solver performance differences.

Keywords

Transportation Metaheuristics Combinatorial optimization TSP Instance hardness 

Notes

Acknowledgments

The authors acknowledge support by the European Research Center for Information Systems (ERCIS).

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Information Systems and Statistics GroupUniversity of MünsterMünsterGermany

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