Skip to main content

2018 | OriginalPaper | Buchkapitel

Bat Algorithm with Individual Local Search

verfasst von : Maoqing Zhang, Zhihua Cui, Yu Chang, Yeqing Ren, Xingjuan Cai, Hui Wang

Erschienen in: Intelligence Science II

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Bat algorithm (BA) is a well-known heuristic algorithm, and has been applied to many practical problems. However, the local search method employed in BA has the shortcoming of premature convergence, and does not perform well in early search stage. To avoid this issue, this paper proposes a new update method for local search. To verify the proposed method, this paper employs CEC2013 test suit to test it with PSO and standard BA as comparison algorithms. Experimental results demonstrate that the proposed method obviously outperforms other algorithms and exhibits better performance.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: International Symposium on MICRO Machine and Human Science, pp. 39–43. IEEE (2002) Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: International Symposium on MICRO Machine and Human Science, pp. 39–43. IEEE (2002)
2.
Zurück zum Zitat Dorigo, M., Birattari, M., Stutzle, T.: Ant colony optimization. IEEE Comput. Intell. Mag. 1(4), 28–39 (2007)CrossRef Dorigo, M., Birattari, M., Stutzle, T.: Ant colony optimization. IEEE Comput. Intell. Mag. 1(4), 28–39 (2007)CrossRef
3.
Zurück zum Zitat Xu, B., Zhu, J., Chen, Q.: Ant Colony Optimization, New Advances in Machine Learning, pp. 1155–1173. InTech (2010) Xu, B., Zhu, J., Chen, Q.: Ant Colony Optimization, New Advances in Machine Learning, pp. 1155–1173. InTech (2010)
4.
Zurück zum Zitat Yang, X.S.: A new metaheuristic bat-inspired algorithm. Comput. Knowl. Technol. 284, 65–74 (2010)MATH Yang, X.S.: A new metaheuristic bat-inspired algorithm. Comput. Knowl. Technol. 284, 65–74 (2010)MATH
5.
Zurück zum Zitat Yang, X.S., Deb, S.: Cuckoo Search via Lévy flights. In: Nature & Biologically Inspired Computing, NaBIC 2009, vol. 2010, pp. 210–214 (2009) Yang, X.S., Deb, S.: Cuckoo Search via Lévy flights. In: Nature & Biologically Inspired Computing, NaBIC 2009, vol. 2010, pp. 210–214 (2009)
6.
Zurück zum Zitat Zhang, M., Wang, H., Cui, Z., et al.: Hybrid multi-objective cuckoo search with dynamical local search. Memet. Comput. 10(2), 199–208 (2018)CrossRef Zhang, M., Wang, H., Cui, Z., et al.: Hybrid multi-objective cuckoo search with dynamical local search. Memet. Comput. 10(2), 199–208 (2018)CrossRef
7.
Zurück zum Zitat Cui, Z., Sun, B., et al.: A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physical systems. J. Parallel Distrib. Comput. 103, 42–52 (2017)CrossRef Cui, Z., Sun, B., et al.: A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physical systems. J. Parallel Distrib. Comput. 103, 42–52 (2017)CrossRef
8.
Zurück zum Zitat Yang, X.S.: Firefly algorithms for multimodal optimization. Mathematics 5792, 169–178 (2009)MathSciNetMATH Yang, X.S.: Firefly algorithms for multimodal optimization. Mathematics 5792, 169–178 (2009)MathSciNetMATH
9.
Zurück zum Zitat Nasiri, B., Meybodi, M.R.: History-driven firefly algorithm for optimisation in dynamic and uncertain environments. Int. J. Bio Inspired Comput. 8(5), 326–339 (2016)CrossRef Nasiri, B., Meybodi, M.R.: History-driven firefly algorithm for optimisation in dynamic and uncertain environments. Int. J. Bio Inspired Comput. 8(5), 326–339 (2016)CrossRef
10.
Zurück zum Zitat Gao, M.L., Shen, J., Yin, L.J., et al.: A novel visual tracking method using bat algorithm. Neurocomputing 177, 612–619 (2016)CrossRef Gao, M.L., Shen, J., Yin, L.J., et al.: A novel visual tracking method using bat algorithm. Neurocomputing 177, 612–619 (2016)CrossRef
12.
Zurück zum Zitat Cui, Z., Xue, F., et al.: Detection of malicious code variants based on deep learning. IEEE Trans. Ind. Inf. 14(7), 3187–3196 (2018)CrossRef Cui, Z., Xue, F., et al.: Detection of malicious code variants based on deep learning. IEEE Trans. Ind. Inf. 14(7), 3187–3196 (2018)CrossRef
13.
Zurück zum Zitat Luo, Q., Li, L., Zhou, Y.: A quantum encoding bat algorithm for uninhabited combat aerial vehicle path planning. Int. J. Innov. Comput. Appl. 8(3), 182–193 (2017)CrossRef Luo, Q., Li, L., Zhou, Y.: A quantum encoding bat algorithm for uninhabited combat aerial vehicle path planning. Int. J. Innov. Comput. Appl. 8(3), 182–193 (2017)CrossRef
14.
Zurück zum Zitat Marichelvam, M.K., Prabaharan, T., Yang, X.S., et al.: Solving hybrid flow shop scheduling problems using bat algorithm. Int. J. Logist. Econ. Glob. 5(1), 15–29 (2013) Marichelvam, M.K., Prabaharan, T., Yang, X.S., et al.: Solving hybrid flow shop scheduling problems using bat algorithm. Int. J. Logist. Econ. Glob. 5(1), 15–29 (2013)
15.
Zurück zum Zitat Tosun, Ö., Marichelvam, M.K.: Hybrid bat algorithm for flow shop scheduling problems. Int. J. Math. Oper. Res. 9(1), 125–138 (2016)MathSciNetCrossRef Tosun, Ö., Marichelvam, M.K.: Hybrid bat algorithm for flow shop scheduling problems. Int. J. Math. Oper. Res. 9(1), 125–138 (2016)MathSciNetCrossRef
16.
Zurück zum Zitat Dao, T.K., Pan, T.S., Nguyen, T.T., et al.: Parallel bat algorithm for optimizing makespan in job shop scheduling problems. J. Intell. Manuf. 29(2), 1–12 (2015) Dao, T.K., Pan, T.S., Nguyen, T.T., et al.: Parallel bat algorithm for optimizing makespan in job shop scheduling problems. J. Intell. Manuf. 29(2), 1–12 (2015)
18.
Zurück zum Zitat Wang, G., Guo, L., Hong, D., et al.: A bat algorithm with mutation for UCAV path planning. Sci. World J. 6, 418946 (2012) Wang, G., Guo, L., Hong, D., et al.: A bat algorithm with mutation for UCAV path planning. Sci. World J. 6, 418946 (2012)
19.
Zurück zum Zitat Fister Jr., I., Fong, S., Brest, J., et al.: A novel hybrid self-adaptive bat algorithm. Sci. World J. 2014(1–2), 709–738 (2014) Fister Jr., I., Fong, S., Brest, J., et al.: A novel hybrid self-adaptive bat algorithm. Sci. World J. 2014(1–2), 709–738 (2014)
21.
Zurück zum Zitat Al-Betar, M.A., Awadallah, M.A., Faris, H., et al.: Bat-inspired algorithms with natural selection mechanisms for global optimization. Neurocomputing 273, 448–465 (2017)CrossRef Al-Betar, M.A., Awadallah, M.A., Faris, H., et al.: Bat-inspired algorithms with natural selection mechanisms for global optimization. Neurocomputing 273, 448–465 (2017)CrossRef
22.
Zurück zum Zitat Cai, X., Wang, H., et al.: Bat algorithm with triangle-flipping strategy for numerical optimization. Int. J. Mach. Learn. Cybern. 9(2), 199–215 (2018)CrossRef Cai, X., Wang, H., et al.: Bat algorithm with triangle-flipping strategy for numerical optimization. Int. J. Mach. Learn. Cybern. 9(2), 199–215 (2018)CrossRef
23.
Zurück zum Zitat Cai, X., Gao, X., Xue, Y.: Improved bat algorithm with optimal forage strategy and random disturbance strategy. Int. J. Bio Inspired Comput. 8(4), 205–214 (2016)CrossRef Cai, X., Gao, X., Xue, Y.: Improved bat algorithm with optimal forage strategy and random disturbance strategy. Int. J. Bio Inspired Comput. 8(4), 205–214 (2016)CrossRef
24.
Zurück zum Zitat Liang, J.J., Runarsson, T.P., Mezura-Montes, E., et al.: Problem definitions and evaluation criteria for the CEC 2006. Technical report, Nanyang Technological University, Singapore (2006) Liang, J.J., Runarsson, T.P., Mezura-Montes, E., et al.: Problem definitions and evaluation criteria for the CEC 2006. Technical report, Nanyang Technological University, Singapore (2006)
Metadaten
Titel
Bat Algorithm with Individual Local Search
verfasst von
Maoqing Zhang
Zhihua Cui
Yu Chang
Yeqing Ren
Xingjuan Cai
Hui Wang
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-030-01313-4_47

Premium Partner