Abstract
Firefly algorithm is a new meta-heuristic inspired by a natural phenomenon of fireflies’ flashing light. Firefly algorithm has been successfully applied to solve several optimization problems. However, It still suffers from some drawbacks such as easily getting stuck at local optima and slow speed of convergence. This paper proposes a new hybrid variant of discrete firefly algorithm, called HDFA, to solve traveling salesman problem (TSP). In the proposed improvement, the balance between intensification and diversification is achieved by utilizing the local search procedures, 2-opt and 3-opt, to improve searching performance and speed up the convergence. In addition, the genetic algorithm operators, crossover and mutation, are added to allow performance of both local and global search respectively. The validity of HDFA is verified by comparative experiments using eighteen TSP benchmark instances from TSBLIB and compared to some well-known algorithms. Results in the conducted experiments show that HDFA has significantly better performance than the performance of compared algorithms for all instances in terms of solution quality.
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References
R. Matai, S.P. Singh, M.L. Mittal, Traveling Salesman Problem, Theory and Applications pp. 1–24 (2010)
C. Chauhan, R. Gupta, K. Pathak, International Journal of Computer Applications 52(4) (2012)
C.H. Papadimitriou, Computational complexity (John Wiley and Sons Ltd., 2003)
X.S. Yang, Scholarpedia 6(8), 11472 (2011)
I. Fister, X.S. Yang, J. Brest, Swarm and Evolutionary Computation 13, 34 (2013)
I. Fister, X.S. Yang, D. Fister, I. Fister Jr, in Cuckoo Search and Firefly Algorithm (Springer, 2014), pp. 347–360
B. Rampriya, K. Mahadevan, S. Kannan, in Communication Control and Computing Technologies (ICCCCT), 2010 IEEE International Conference on (IEEE, 2010), pp. 389–393
S.M. Farahani, A.A. Abshouri, B. Nasiri, M. Meybodi, International Journal of Artificial Intelligence 8(12), 97 (2012)
A. Abdullah, S. Deris, M.S. Mohamad, S.Z.M. Hashim, in Distributed Computing and Artificial Intelligence (Springer, 2012), pp. 673–680
A. Rajini, V.K. David, Int. J. Comput. Appl 30(6), 10 (2011)
X.S. Yang, S. Deb, in Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) (Springer, 2010), pp. 101–111
G.K. Jati, et al., Evolutionary discrete firefly algorithm for travelling salesman problem (Springer, 2011)
M. SARAEI, R. ANALOUEI, P. MANSOURI, Cumhuriyet Science Journal 36(6), 267 (2015)
L. Zhou, L. Ding, X. Qiang, in Bio-Inspired Computing-Theories and Applications (Springer, 2014), pp. 648–653
L. Zhou, L. Ding, X. Qiang, Y. Luo, Journal of Computational and Theoretical Nanoscience 12(7), 1184 (2015)
X.S. Yang, Nature-inspired metaheuristic algorithms (Luniver press, 2010)
X.S. Yang, Engineering optimization: an introduction with metaheuristic applications (John Wiley & Sons, 2010)
E. Osaba, X.S. Yang, F. Diaz, P. Lopez-Garcia, R. Carballedo, Engineering Applications of Artificial Intelligence 48, 59 (2016)
P. Thakur, A.J. Singh, International Journal of Advanced Research in Computer Science and Software Engineering 4(3) (2014)
Y. Saji, M.E. Riffi, Neural Computing and Applications pp. 1–14 (2015)
G. Jati, R. Manurung, Discrete firefly algorithm for traveling salesman problem: A new movement scheme. Swarm Intelligence and Bio-Inspired Computation: Theory and Applications pp. 295–312
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Mohsen, A.M., Al-Sorori, W. (2017). A New Hybrid Discrete Firefly Algorithm for Solving the Traveling Salesman Problem. In: Lee, R. (eds) Applied Computing and Information Technology. Studies in Computational Intelligence, vol 695. Springer, Cham. https://doi.org/10.1007/978-3-319-51472-7_12
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DOI: https://doi.org/10.1007/978-3-319-51472-7_12
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