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Annals of Operations Research

, Volume 254, Issue 1–2, pp 111–130 | Cite as

Proper balance between search towards and along Pareto front: biobjective TSP case study

  • Andrzej Jaszkiewicz
  • Thibaut LustEmail author
Original Paper

Abstract

In this paper we propose simple yet efficient version of the two-phase Pareto local search (2PPLS) for solving the biobjective traveling salesman problem (bTSP). In the first phase the powerful Lin–Kernighan heuristic is used to generate some high quality solutions being very close to the Pareto front. Then Pareto local search is used to generate more potentially Pareto efficient solutions along the Pareto front. Instead of previously used method of Aneja and Nair we use uniformly distributed weight vectors in the first phase. We show experimentally that properly balancing the computational effort in the first and second phase we can obtain results better than previous versions of 2PPLS for bTSP and at least comparable to the state-of-the art results of more complex MOMAD method. Furthermore, we propose a simple extension of 2PPLS where some additional solutions are generated by Lin–Kernighan heuristic during the run of PLS. In this way we obtain a method that is more robust with respect to the number of initial solutions generated in the first phase.

Keywords

Multiobjective optimization Pareto local search Traveling salesman problem 

Notes

Acknowledgements

The research of Andrzej Jaszkiewicz was funded by the the Polish National Science Center, Grant No. UMO-2013/11/B/ST6/01075.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Faculty of Computing, Institute of Computing SciencePoznan University of TechnologyPoznanPoland
  2. 2.CNRS, LIP6, UMR 7606Sorbonne Universités, UPMC Universités Paris 06ParisFrance

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