R. Eberhart and J. Kennedy, A new optimizer using particle swarm theory, International Symposium on MICRO Machine and Human Science, pp.39-43, 2002.

M. Dorigo, M. Birattari, and T. Stutzle, Ant colony optimization, IEEE Computational Intelligence Magazine, vol.1, issue.4, pp.28-39, 2007.

B. Xu, J. Zhu, and Q. Chen, Ant Colony Optimization, New Advances in Machine Learning, pp.1155-1173, 2010.

X. Yang, A New Metaheuristic Bat-Inspired Algorithm, Computer Knowledge & Technology, vol.284, pp.65-74, 2010.

X. Yang and D. S. , Cuckoo Search via Lé vy flights, Nature & Biologically Inspired Computing, pp.210-214, 2009.
DOI : 10.1109/nabic.2009.5393690

M. Zhang, H. Wang, and Z. Cui, Hybrid multi-objective cuckoo search with dynamical local search, Memetic Computing, vol.10, issue.2, pp.199-208, 2018.

Z. Cui and B. Sun, A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physical systems, Journal of Parallel and Distributed Computing, vol.103, pp.42-52, 2017.

X. Yang, Firefly Algorithms for Multimodal Optimization. Mathematics, vol.5792, pp.169-178, 2009.

B. Nasiri and M. R. Meybodi, History-driven firefly algorithm for optimisation in dynamic and uncertain environments, International Journal of Bio-Inspired Computation, vol.8, issue.5, pp.326-339, 2016.

M. Gao, J. Shen, and L. Yin, A novel visual tracking method using bat algorithm, Neurocomputing, vol.177, pp.612-619, 2016.

L. Pham, T. Ho, and T. Nguyen, Modified Bat Algorithm for Combined Economic and Emission Dispatch Problem, Proceedings of the International Conference on Advances in Electrical Engineering and Related Sciences, 2016.

Z. Cui and F. Xue, Detection of malicious code variants based on deep learning, IEEE Transactions on Industrial Informatics, vol.14, issue.7, pp.3187-3196, 2018.

Q. Luo, L. Li, and Y. Zhou, A quantum encoding bat algorithm for uninhabited combat aerial vehicle path planning, International Journal of Innovative Computing and Applications, vol.8, issue.3, pp.182-193, 2017.

M. Marichelvam, T. Prabaharan, and X. Yang, Solving hybrid flow shop scheduling problems using bat algorithm, International Journal of Logistics Economics & Globalisation, vol.5, issue.1, pp.15-29, 2013.
DOI : 10.1504/ijleg.2013.054428

M. K. Ömür-tosun, Hybrid bat algorithm for flow shop scheduling problems, International Journal of Mathematics in Operational Research, vol.9, issue.1, pp.125-138, 2016.

T. Dao, T. Pan, and T. Nguyen, Parallel bat algorithm for optimizing makespan in job shop scheduling problems, Journal of Intelligent Manufacturing, vol.29, issue.2, pp.1-12, 2015.

A. Gandomi and X. Yang, Chaotic bat algorithm, Journal of Computational Science, vol.5, issue.2, pp.224-232, 2014.
DOI : 10.1016/j.jocs.2013.10.002

G. Wang, L. Guo, and D. Hong, A Bat Algorithm with Mutation for UCAV Path Planning, The Scientific World Journal, issue.6, p.418946, 2012.

F. Jr, S. Fong, and J. Brest, A novel hybrid self-adaptive bat algorithm. The scientific world journal, pp.709-738, 2014.

Z. Cui, Y. Cao, and X. Cai, Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things, Journal of Parallel & Distributed Computing, 2017.

A. , A. , M. Faris, and H. , Bat-inspired Algorithms with Natural Selection mechanisms for Global optimization, Neurocomputing, 2017.

X. Cai and H. Wang, Bat algorithm with triangle-flipping strategy for numerical optimization, International Journal of Machine Learning and Cybernetics, vol.9, issue.2, pp.199-215, 2018.

X. Cai, X. Gao, and Y. Xue, Improved bat algorithm with optimal forage strategy and random disturbance strategy, International Journal of Bio-inspired Computation, vol.8, issue.4, pp.205-214, 2016.
DOI : 10.1504/ijbic.2016.078666

J. Liang, T. Runarsson, and E. Mezura-montes, Problem definitions and evaluation criteria for the CEC 2006 special session on constrained real-parameter optimization, International Journal of Computer Assisted Radiology & Surgery, 2005.