Comparative Analysis of Swarm-Based Metaheuristic Algorithms on Benchmark Functions

  • Kashif Hussain
  • Mohd Najib Mohd SallehEmail author
  • Shi Cheng
  • Yuhui Shi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10385)


Swarm-based metaheuristic algorithms inspired from swarm systems in nature have produced remarkable results while solving complex optimization problems. This is due to their capability of decentralized control of search agents able to explore search environment more effectively. The large number of metaheuristics sometimes puzzle beginners and practitioners where to start with. This experimental study covers 10 swarm-based metaheuristic algorithms introduced in last decade to be investigated on their performances on 12 test functions of high dimensions with diverse features of modality, scalability, and valley landscape. Based on simulations, it can be concluded that firefly algorithm outperformed rest of the algorithms while tested unimodal functions. On multimodal functions, animal migration algorithm produced outstanding results as compared to rest of the methods. In future, further investigation can be conducted on relating benchmark functions to real-world optimization problem so that metaheuristic algorithms can be grouped according to suitability of problem characteristics.


Swarm-intelligence Swarm-based algorithms Metaheuristic Benchmark functions 



The authors would like to thank Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia for supporting this research under Postgraduate Incentive Research Grant, Vote No. U560.


  1. 1.
    Amudhavel, J., Kumarakrishnan, S., Anantharaj, B., Padmashree, D., Harinee, S., Kumar, K.P.: A novel bio-inspired krill herd optimization in wireless ad-hoc network (WANET) for effective routing. In: Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering & Technology (ICARCSET 2015), p. 28. ACM (2015)Google Scholar
  2. 2.
    Askarzadeh, A.: A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput. Struct. 169, 1–12 (2016)CrossRefGoogle Scholar
  3. 3.
    Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Report, Technical report-tr06, Erciyes University, Engineering Faculty, Computer Engineering Department (2005)Google Scholar
  4. 4.
    Li, X., Zhang, J., Yin, M.: Animal migration optimization: an optimization algorithm inspired by animal migration behavior. Neural Comput. Appl. 24(7–8), 1867–1877 (2014)CrossRefGoogle Scholar
  5. 5.
    Meng, X., Liu, Y., Gao, X., Zhang, H.: A new bio-inspired algorithm: chicken swarm optimization. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds.) ICSI 2014. LNCS, vol. 8794, pp. 86–94. Springer, Cham (2014). doi: 10.1007/978-3-319-11857-4_10 Google Scholar
  6. 6.
    Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)CrossRefGoogle Scholar
  7. 7.
    Shi, Y.: Brain storm optimization algorithm. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011. LNCS, vol. 6728, pp. 303–309. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-21515-5_36 CrossRefGoogle Scholar
  8. 8.
    Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)CrossRefGoogle Scholar
  9. 9.
    Wang, G.G., Deb, S., dos Coelho, L.S.: Elephant herding optimization. In: 2015 3rd International Symposium on Computational and Business Intelligence (ISCBI), pp. 1–5. IEEE (2015)Google Scholar
  10. 10.
    Yang, X.S.: Firefly algorithm. In: Nature-Inspired Metaheuristic Algorithms, vol. 20, pp. 79–90 (2008)Google Scholar
  11. 11.
    Yang, X.S.: A New Metaheuristic Bat-Inspired Algorithm, pp. 65–74. Springer, Heidelberg (2010)Google Scholar
  12. 12.
    Zhang, L., Liu, L., Yang, X.S., Dai, Y.: A novel hybrid firefly algorithm for global optimization. PLoS ONE 11(9), e0163230 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Kashif Hussain
    • 1
  • Mohd Najib Mohd Salleh
    • 1
    Email author
  • Shi Cheng
    • 2
  • Yuhui Shi
    • 3
  1. 1.Universiti Tun Hussein Onn MalaysiaBatu PahatMalaysia
  2. 2.School of Computer ScienceShaanxi Normal UniversityXianChina
  3. 3.Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina

Personalised recommendations