1. Sotiroudis, S.P., Goudos, S.K., Gotsis, K.A., Siakavara, K., Sahalos, J.N.: Application of a composite differential evolution algorithm in optimal neural network design for propagation path-loss prediction in mobile communication systems. IEEE Antennas Wirel. Propag. Lett.12, 364–367 (2013)

   Article  Google Scholar 

2. Goudos, S.K., Gotsis, K.A., Siakavara, K., Vafiadis, E.E., Sahalos, J.N.: A multi-objective approach to subarrayed linear antenna arrays design based on memetic differential evolution. IEEE Trans. Antennas Propag.61(6), 3042–3052 (2013)

   Article MathSciNet  Google Scholar 

3. Pantoja, M.F., Bretones, A.R., Ruiz, F.G., Garcia, S.G., Martin, R.G.: Particle-swarm optimization in antenna design: optimization of log-periodic dipole arrays. IEEE Antennas Propag. Mag.49(4), 34–47 (2007)

   Article  Google Scholar 

4. Bozza, G., Pastorino, M., Raffetto, M., Randazzo, A.: Synthesis of metamaterial coatings for cylindrical structures by an ant-colony optimization algorithm. In: Proceedings of the 2006 IEEE International Workshop on Imagining Systems and Techniques, pp. 143–147 (2006)

   Google Scholar 

5. Chen, P.Y., Chen, C.H., Wang, H., Tsai, J.H., Ni, W.X.: Synthesis design of artificial magnetic metamaterials using a genetic algorithm. Opt. Express16(17), 12806–12818 (2008)

   Article  Google Scholar 

6. Di Cesare, N., Chamoret, D., Domaszewski, M.: Optimum topological design of negative permeability dielectric metamaterial using a new binary particle swarm algorithm. Adv. Eng. Softw.101, 149–159 (2016)

   Article  Google Scholar 

7. Storn, R., Price, K.: Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim.11(4), 341–359 (1997)

   Article MathSciNet  Google Scholar 

8. Zhao, J., Lv, L., Wang, H., Sun, H., Wu, R., Nie, J., Xie, Z.: Particle swarm optimization based on vector Gaussian learning. KSII Trans. Internet Inf. Syst.11(4), 2038–2057 (2017)

   Google Scholar 

9. Wang, H., Sun, H., Li, C.H., Rahnamayan, S., Pan, J.S.: Diversity enhanced particle swarm optimization with neighborhood search. Inf. Sci.223, 119–135 (2013)

   Article MathSciNet  Google Scholar 

10. Sun, H., Wang, K., Zhao, J., Yu, X.: Artificial bee colony algorithm with improved special centre. Int. J. Comput. Sci. Math.7(6), 548–553 (2016)

    Article MathSciNet  Google Scholar 

11. Yu, G.: A new multi-population-based artificial bee colony for numerical optimization. Int. J. Comput. Sci. Math.7(6), 509–515 (2016)

    Article MathSciNet  Google Scholar 

12. Lv, L., Wu, L.Y., Zhao, J., Wang, H., Wu, R.X., Fan, T.H., Hu, M., Xie, Z.F.: Improved multi-strategy artificial bee colony algorithm. Int. J. Comput. Sci. Math.7(5), 467–475 (2016)

    Article MathSciNet  Google Scholar 

13. Wang, H., Wu, Z.J., Rahnamayan, S., Sun, H., Liu, Y., Pan, J.S.: Multi-strategy ensemble artificial bee colony algorithm. Inf. Sci.279, 587–603 (2014)

    Article MathSciNet  Google Scholar 

14. Zhou, X.Y., Wang, H., Wang, M.W., Wan, J.Y.: Enhancing the modified artificial bee colony algorithm with neighborhood search. Soft. Comput.21(10), 2733–2743 (2017)

    Article  Google Scholar 

15. Cui, Z., Sun, B., Wang, G., Xue, Y., Chen, J.: A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physical systems. J. Parallel Distrib. Comput.103, 42–52 (2017)

    Article  Google Scholar 

16. Zhang, M., Wang, H., Cui, Z., Chen, J.: Hybrid multi-objective cuckoo search with dynamical local search. Memet. Comput. (2017, in press).https://doi.org/10.1007/s12293-017-0237-2

17. Yu, G.: An improved firefly algorithm based on probabilistic attraction. Int. J. Comput. Sci. Math.7(6), 530–536 (2016)

    Article MathSciNet  Google Scholar 

18. Wang, H., Cui, Z., Sun, H., Rahnamayan, S., Yang, X.S.: Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism. Soft. Comput.21(18), 5325–5339 (2017)

    Article  Google Scholar 

19. Lv, L., Zhao, J.: The firefly algorithm with Gaussian disturbance and local search. J. Signal Process. Syst. (2017, in press).https://doi.org/10.1007/s11265-017-1278-y

20. Wang, H., Wang, W., Sun, H., Rahnamayan, S.: Firefly algorithm with random attraction. Int. J. Bio-Inspired Comput.8(1), 33–41 (2016)

    Article  Google Scholar 

21. Kaur, M., Sharma, P.K.: On solving partition driven standard cell placement problem using firefly-based metaheuristic approach. Int. J. Bio-Inspired Comput.9(2), 121–127 (2017)

    Article  Google Scholar 

22. Wang, H., Wang, W.J., Zhou, X.Y., Sun, H., Zhao, J., Yu, X., Cui, Z.: Firefly algorithm with neighborhood attraction. Inf. Sci.382–383, 374–387 (2017)

    Article  Google Scholar 

23. Wang, H., Zhou, X.Y., Sun, H., Yu, X., Zhao, J., Zhang, H., Cui, L.Z.: Firefly algorithm with adaptive control parameters. Soft. Comput.21(17), 5091–5102 (2017)

    Article  Google Scholar 

24. Cai, X., Gao, X.Z., Xue, Y.: Improved bat algorithm with optimal forage strategy and random disturbance strategy. Int. J. Bio-Inspired Comput.8(4), 205–214 (2016)

    Article  Google Scholar 

25. Bantin, C., Balmain, K.: Study of compressed log-periodic dipole antennas. IEEE Trans. Antennas Propag.18(2), 195–203 (1970)

    Article  Google Scholar 

26. Li, X., Zhang, X., Hei, Y.: Antenna Gain Imbalance detection method using Particle Swarm algorithm for MIMO systems. In: International Conference on Wireless Communications and Signal Processing (WCSP), pp. 1–6, October 2012

    Google Scholar 

27. Pu, T.L., Huang, K.M., Wang, B., Yang, Y.: Application of micro-genetic algorithm to the design of matched high gain patch antenna with zero-refractive-index metamaterial lens. J. Electromagn. Waves Appl.24(8–9), 1207–1217 (2010)

    Article  Google Scholar 

28. Wang, H., Rahnamayan, S., Sun, H., Omran, M.G.H.: Gaussian bare-bones differential evolution. IEEE Trans. Cybern.43(2), 634–647 (2013)

    Article  Google Scholar 

29. Zhou, X.Y., Wu, Z.J., Wang, H., Rahnamayan, S.: Enhancing differential evolution with role assignment scheme. Soft. Comput.18(11), 2209–2225 (2014)

    Article  Google Scholar 

30. Wang, H., Rahnamayan, S., Wu, Z.J.: Parallel differential evolution with self-adapting control parameters and generalized opposition-based learning for solving high-dimensional optimization problems. J. Parallel Distrib. Comput.73(1), 62–73 (2013)

    Article  Google Scholar 

31. Wang, H., Wu, Z.J., Rahnamayan, S.: Enhanced opposition-based differential evolution for high-dimensional optimization problems. Soft. Comput.15(11), 2127–2140 (2011)

    Article  Google Scholar 

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