A hyperheuristic approach based on low-level heuristics for the travelling thief problem

  • Mohamed El Yafrani
  • Marcella Martins
  • Markus Wagner
  • Belaïd Ahiod
  • Myriam Delgado
  • Ricardo Lüders
Article
  • 307 Downloads
Part of the following topical collections:
  1. Special Issue on Automated Design and Adaptation of Heuristics for Scheduling and Combinatorial Optimisation

Abstract

In this paper, we investigate the use of hyper-heuristics for the travelling thief problem (TTP). TTP is a multi-component problem, which means it has a composite structure. The problem is a combination between the travelling salesman problem and the knapsack problem. Many heuristics were proposed to deal with the two components of the problem separately. In this work, we investigate the use of automatic online heuristic selection in order to find the best combination of the different known heuristics. In order to achieve this, we propose a genetic programming based hyper-heuristic called GPHS*, and compare it to state-of-the-art algorithms. The experimental results show that the approach is competitive with those algorithms on small and mid-sized TTP instances.

Keywords

Heuristic selection Genetic programming Travelling thief problem Multi-component problems 

Notes

Acknowledgements

M. Martins acknowledges CAPES/Brazil. M. Delgado acknowledges CNPq Grant Nos.: 309197/2014-7 (Brazil Government).

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.LRIT, associated unit to CNRST (URAC 29)Mohammed V University in RabatRabatMorocco
  2. 2.Optimisation and Logistics, School of Computer ScienceUniversity of AdelaideAdelaideAustralia
  3. 3.Federal University of Technology - Paraná (UTFPR)CuritibaBrazil

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