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Soft Computing

, Volume 22, Issue 22, pp 7619–7631 | Cite as

Applications of artificial atom algorithm to small-scale traveling salesman problems

  • Ayse Erdogan Yildirim
  • Ali Karci
Methodologies and Application

Abstract

Most of the meta-heuristic algorithms are based on the natural processes. They were inspired by physical, biological, social, chemical, social–biological, biological–geography, music, and hybrid processes. In this paper, artificial atom algorithm which was inspired by one of natural processes was applied to traveling salesman problem. The obtained results have shown that for small-scale TSP, artificial atom algorithm is closer to optimum than the other compared heuristic algorithms such as tabu search, genetic algorithm, particle swarm optimization, ant colony optimization, and their different combinations.

Keywords

Meta-heuristic approaches Traveling salesman problem Artificial atom algorithm Genetic algorithm Particle swarm optimization Ant colony optimization 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Computer Engineering DepartmentUniversity of FiratElazigTurkey
  2. 2.Computer Engineering DepartmentUniversity of InonuMalatyaTurkey

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