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Multi-population Discrete Bat Algorithm with Crossover to Solve TSP

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Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) (HIS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 552))

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Abstract

Many meta-heuristic algorithms were proposed to solve several optimization problems. A new meta-heuristic bat algorithm (BA), inspired by the echolocation characteristics of micro-bats, has been extensively applied to solve continuous optimization problems. In addition, BA was also adapted to address combinatorial optimization problems. Unfortunately, like its basic version and other meta-heuristic algorithms, the adapted BA still suffers from some drawbacks such as slow speed convergence and easily trapping in local optima. We proposed a new variant of BA, called multi-population discrete bat algorithm (MPDBA), to solve traveling salesman problem (TSP). The validity of MPDBA was verified by comparative experiments using twenty TSP benchmark instances from TSBLIB. The experiments carried out show that MPDBA outperformed other state-of-art algorithms with respect to average and best solutions.

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References

  1. Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. (CSUR) 35(3), 268–308 (2003)

    Article  Google Scholar 

  2. Matai, R., Singh, S.P., Mittal, M.L.: Traveling salesman problem: an overview of applications, formulations, and solution approaches. In: Traveling Salesman Problem, Theory and Applications, pp. 1–24 (2010)

    Google Scholar 

  3. Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 65–74. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  4. Wang, G., Guo, L.: A novel hybrid bat algorithm with harmony search for global numerical optimization. J. Appl. Math. 2013, 1–21 (2013)

    MathSciNet  MATH  Google Scholar 

  5. Nguyen, T.-T., Pan, J.-S., Dao, T.-K., Kuo, M.-Y., Horng, M.-F.: Hybrid bat algorithm with artificial bee colony. In: Pan, J.-S., Snasel, V., Corchado, E.S., Abraham, A., Wang, S.-L. (eds.) Intelligent Data analysis and its Applications, Volume II. AISC, vol. 298, pp. 45–55. Springer, Heidelberg (2014). doi:10.1007/978-3-319-07773-4_5

    Google Scholar 

  6. Pan, T.-S., Dao, T.-K., Nguyen, T.-T., Chu, S.-C.: Hybrid particle swarm optimization with bat algorithm. In: Sun, H., Yang, C.-Y., Lin, C.-W., Pan, J.-S., Snasel, V., Abraham, A. (eds.) Genetic and Evolutionary Computing. AISC, vol. 329, pp. 37–47. Springer, Heidelberg (2015). doi:10.1007/978-3-319-12286-1_5

    Google Scholar 

  7. Meng, X., Gao, X., Liu, Y.: A novel hybrid bat algorithm with differential evolution strategy for constrained optimization. Int. J. Hybrid Inf. Technol. 8(1), 383–396 (2015)

    Article  Google Scholar 

  8. Khan, K., Nikov, A., Sahai, A.: A fuzzy bat clustering method for ergonomic screening of office workplaces. In: Dicheva, D., Markov, Z., Stefanova, E. (eds.) Third International Conference on Software, Services and Semantic Technologies S3T 2011. AINSC, vol. 101, pp. 59–66. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  9. Abdel-Raouf, O., Abdel-Baset, M., El-Henawy, I.: An improved chaotic bat algorithm for solving integer programming problems. Int. J. Mod. Educ. Comput. Sci. (IJMECS) 6(8), 18 (2014)

    Article  Google Scholar 

  10. Gandomi, A.H., Yang, X.-S.: Chaotic bat algorithm. J. Comput. Sci. 5(2), 224–232 (2014)

    Article  MathSciNet  Google Scholar 

  11. Wang, G., Guo, L., Duan, H., Liu, L., Wang, H.: A bat algorithm with mutation for UCAV path planning. Sci. World J. 2012, 1–15 (2012)

    Google Scholar 

  12. Fister Jr., I., Fister, D., Yang, X.-S.: A hybrid bat algorithm. ArXiv e-prints, March 2013

    Google Scholar 

  13. Marichelvam, M., Prabaharan, T., Yang, X.-S., Geetha, M.: Solving hybrid flow shop scheduling problems using bat algorithm. Int. J. Logistics Econ. Globalisation 5(1), 15–29 (2013)

    Article  Google Scholar 

  14. Nakamura, R., Pereira, L., Costa, K., Rodrigues, D., Papa, J., Yang, X.-S.: BBA: a binary bat algorithm for feature selection. In: 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 291–297, August 2012

    Google Scholar 

  15. Raghavan, S., Sarwesh, P., Marimuthu, C., Chandrasekaran, K.: Bat algorithm for scheduling workflow applications in cloud. In: 2015 International Conference on Electronic Design, Computer Networks & Automated Verification (EDCAV), pp. 139–144. IEEE (2015)

    Google Scholar 

  16. Sabba, S., Chikhi, S.: A discrete binary version of bat algorithm for multidimensional knapsack problem. Int. J. Bio-Inspired Comput. 6(2), 140–152 (2014)

    Article  Google Scholar 

  17. Tosun, Ö., Marichelvam, M.: Hybrid bat algorithm for flow shop scheduling problems. Int. J. Math. Oper. Res. 9(1), 125–138 (2016)

    Article  MathSciNet  Google Scholar 

  18. Hassan, E.A., Hafez, A.I., Hassanien, A.E., Fahmy, A.A.: A discrete bat algorithm for the community detection problem. In: Onieva, E., Santos, I., Osaba, E., Quintián, H., Corchado, E. (eds.) HAIS 2015. LNCS (LNAI), vol. 9121, pp. 188–199. Springer, Heidelberg (2015). doi:10.1007/978-3-319-19644-2_16

    Chapter  Google Scholar 

  19. Zhou, Y., Luo, Q., Xie, J., Zheng, H.: A hybrid bat algorithm with path relinking for the capacitated vehicle routing problem. In: Yang, X.-S., Bekdaş, G., Nigdeli, S.M. (eds.) Metaheuristics and Optimization in Civil Engineering. MOST, vol. 7, pp. 255–276. Springer, Heidelberg (2016). doi:10.1007/978-3-319-26245-1_12

    Chapter  Google Scholar 

  20. Saji, Y., Riffi, M.E., Ahiod, B.: Discrete bat-inspired algorithm for travelling salesman problem. In: 2014 Second World Conference on Complex Systems (WCCS), pp. 28–31. IEEE (2014)

    Google Scholar 

  21. Saji, Y., Riffi, M.E.: A novel discrete bat algorithm for solving the travelling salesman problem. Neural Comput. Appl. 27, 1–14 (2015)

    Article  Google Scholar 

  22. Amara, J., Hamdani, T.M., Alimi, A.M.: A new hybrid discrete bat algorithm for traveling salesman problem using ordered crossover and 3-opt operators for bat’s local search. In: 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 154–159. IEEE (2015)

    Google Scholar 

  23. Osaba, E., Yang, X.-S., Diaz, F., Lopez-Garcia, P., Carballedo, R.: An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems. Eng. Appl. Artif. Intell. 48, 59–71 (2016)

    Article  Google Scholar 

  24. Tsai, C.-F., Dao, T.-K., Yang, W.-J., Nguyen, T.-T., Pan, T.-S.: Parallelized bat algorithm with a communication strategy. In: Ali, M., Pan, J.-S., Chen, S.-M., Horng, M.-F. (eds.) IEA/AIE 2014. LNCS (LNAI), vol. 8481, pp. 87–95. Springer, Heidelberg (2014). doi:10.1007/978-3-319-07455-9_10

    Chapter  Google Scholar 

  25. Heraguemi, K.E., Kamel, N., Drias, H.: Multi-population cooperative bat algorithm for association rule mining. In: Núñez, M., Nguyen, N.T., Camacho, D., Trawiński, B. (eds.) ICCCI 2015. LNCS (LNAI), vol. 9329, pp. 265–274. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24069-5_25

    Chapter  Google Scholar 

  26. Jaddi, N.S., Abdullah, S., Hamdan, A.R.: Multi-population cooperative bat algorithm-based optimization of artificial neural network model. Inf. Sci. 294, 628–644 (2015)

    Article  MathSciNet  Google Scholar 

  27. Yang, X.-S., He, X.: Bat algorithm: literature review and applications. Int. J. Bio-Inspired Comput. 5(3), 141–149 (2013)

    Article  Google Scholar 

  28. Goldberg, D.E.: Alleles, loci, and the traveling salesman problem. In: Proceedings of an International Conference on Genetic Algorithms and Their Applications, vol. 154, pp. 154–159. Lawrence Erlbaum, Hillsdale (1985)

    Google Scholar 

  29. Yip, P.P., Pao, Y.-H.: Combinatorial optimization with use of guided evolutionary simulated annealing. IEEE Trans. Neural Netw. 6(2), 290–295 (1995)

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Science and Technology, Sana’a, Yemen

    Wedad Al-Sorori & Abdulqader M. Mohsen

Authors
  1. Wedad Al-Sorori
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  2. Abdulqader M. Mohsen
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Corresponding authors

Correspondence to Wedad Al-Sorori or Abdulqader M. Mohsen .

Editor information

Editors and Affiliations

  1. (MIR Labs), Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

  4. Technopolis Rabat-Shore Rocade, International University of Rabat, Sala el Jadida, Morocco

    Ghita Mezzour

  5. Inst Applied Dept of Electronics, Taffala, University of Sousse, Sousse, Tunisia

    Nizar Rokbani

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Al-Sorori, W., Mohsen, A.M. (2017). Multi-population Discrete Bat Algorithm with Crossover to Solve TSP. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_46

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  • DOI: https://doi.org/10.1007/978-3-319-52941-7_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52940-0

  • Online ISBN: 978-3-319-52941-7

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