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Iterative Cartesian Genetic Programming: Creating General Algorithms for Solving Travelling Salesman Problems

  • Patricia Ryser-WelchEmail author
  • Julian F. Miller
  • Jerry Swan
  • Martin A. Trefzer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9594)

Abstract

Evolutionary algorithms have been widely used to optimise or design search algorithms, however, very few have considered evolving iterative algorithms. In this paper, we introduce a novel extension to Cartesian Genetic Programming that allows it to encode iterative algorithms. We apply this technique to the Traveling Salesman Problem to produce human-readable solvers which can be then be independently implemented. Our experimental results demonstrate that the evolved solvers scale well to much larger TSP instances than those used for training.

Keywords

Iterative algorithms Cartesian Genetic Programming TSP 

Notes

Acknowledgements

The N8 HPC computer cluster used to host our evolutionary cross-domain hyper-heuristics and test their performance was provided and funded by the N8 consortium and EPSRC (Grant No.EP/K000225/1). The Centre is co-ordinated by the Universities of Leeds and Manchester.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Patricia Ryser-Welch
    • 1
    Email author
  • Julian F. Miller
    • 1
  • Jerry Swan
    • 1
  • Martin A. Trefzer
    • 1
  1. 1.The University of YorkHeslingtonUK

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