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A Comparative Study of Different Variants of a Memetic Algorithm for ATSP

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10449)

Abstract

In this paper we present a computational study of how different local search methods and the choice of an algorithm stage in which they are applied affect the performance of Memetic Algorithm (MA) solving Asymmetric Traveling Salesman Problem (ATSP). This study contains a comparison of quality of solutions obtained (both in terms of the value of the objective function and the performance time of the method) by sixteen variants of the Memetic Algorithm. Considerable amount of a given problem’s instance and Wilcoxon Signed-Rank Test were used to ensure the impartiality of gained results.

Keywords

Memetic algorithm Asymmetric Travelling Salesman Problem Metaheuristics 

References

  1. 1.
    Castillo, P., Arenas, M., Castellano, J., Merelo, J., Prieto, A., Rivas, V., Romero, G.: Lamarckian Evolution and the Baldwin Effect in Evolutionary Neural Networks (2006). http://www.arxiv.org/PS_cache/cs/pdf/0603/0603004v1.pdf
  2. 2.
    Dawkins, R.: The Selfish Gene. Oxford University Press, Oxford (1976)Google Scholar
  3. 3.
    Dib, O., Manier, M., Caminada, A.: Memetic algorithm for computing shortest paths in multimodal transportation networks. Transp. Res. Procedia 10, 745–755 (2015)CrossRefGoogle Scholar
  4. 4.
    Held, M., Hoffman, A., Johnson, E., Wolfe, P.: Aspects of the traveling salesman problem. IBM J. Res. Dev. 28(4), 476–486 (1984)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Larranaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I., Dizdarevic, S.: Genetic algorithms for the travelling salesman problem: a review of representations and operators. Artif. Intell. Rev. 13(2), 129–170 (1999)CrossRefGoogle Scholar
  6. 6.
    Lau, H., Agussurja, L., Cheng, S., Pang Jin, T.: A multi-objective memetic algorithm for vehicle resource allocation in sustainable transportation planning. In: International Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, China, 3–9 August 2013, pp. 2833–2839 (2013)Google Scholar
  7. 7.
    Moscato, P.: On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts - Towards Memetic Algorithms (1989)Google Scholar
  8. 8.
    Mrowczynska, B., Nowakowski, P.: Optymalizacja tras przejazdu przy zbiorce zuzytego sprzetu elektrycznego i elektronicznego dla zadanych lokalizacji punktow zbiorki. Czasopismo Logistyka 2, 593–604 (2015)Google Scholar
  9. 9.
    Pataki, G.: The bad and the good-and-ugly: formulations for the traveling salesman problem. Technical report CORC 2000–1 (2000)Google Scholar
  10. 10.
    Shaikh, M., Panchal, M.: Solving asymmetric travelling salesman problem using memetic algorithm. Int. J. Emerg. Technol. Adv. Eng. 2(11), 634–639 (2012)Google Scholar
  11. 11.
    Syberfeldt, A., Rogstrom, J., Geertsen, A.: Simulation-based optimization of a real-world travelling salesman problem using an evolutionary algorithm with a repair function. Int. J. Artif. Intell. Expert Syst. (IJAE) 6(3), 27–39 (2015)Google Scholar
  12. 12.
    Zakir, A.: Genetic algorithm for the traveling salesman problem using sequential constructive crossover operator. Int. J. Biometrics Bioinform. (IJBB) 3(6), 96–105 (2010)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Computer ScienceUniversity of SilesiaSosnowiecPoland

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