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A hybrid random-key genetic algorithm for a symmetric travelling salesman problem

Author

Listed:
  • Funda Samanlioglu
  • Mary Beth Kurz
  • William G. Ferrell
  • Sarat Tangudu

Abstract

This paper describes a methodology that finds approximate and sometimes optimal solutions to the symmetric Travelling Salesman Problem (TSP) using a hybrid approach that combines a Random-Key Genetic Algorithm (RKGA) with a local search procedure. The random keys representation ensures that feasible tours are constructed during the application of genetic operators, whereas the genetic algorithm approach with local search efficiently generates optimal or near-optimal solutions. The results of experiments are provided that use examples taken from a well-known online library to confirm the quality of the proposed algorithm.

Suggested Citation

  • Funda Samanlioglu & Mary Beth Kurz & William G. Ferrell & Sarat Tangudu, 2007. "A hybrid random-key genetic algorithm for a symmetric travelling salesman problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 2(1), pages 47-63.
    • Handle: RePEc:ids:ijores:v:2:y:2007:i:1:p:47-63
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