R. Storn and K. Price, Differential Evolution -A Simple and Efficient Heuristic for global Optimization over Continuous Spaces, Journal of Global Optimization, vol.11, issue.4, pp.341-359, 1997.

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

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

S. Mirjalili, Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, vol.89, pp.228-249, 2015.

S. Mirjalili, S. Mirjalili, L. A. Grey-wolf, and . Optimizer, Advances in Engineering Software, vol.69, pp.46-61, 2014.

X. Yang and D. S. , Cuckoo Search via Levy Flights. Mathematics, pp.210-214, 2010.

S. Mirjalili, A. Gandomi, S. Mirjalili, S. Saremi, H. Faris et al., Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems, Advances in Engineering Software, vol.114, pp.163-191, 2017.

X. Yang, Appendix A: Test Problems in Optimization. Engineering Optimization, pp.261-266, 2010.

K. Tang, X. Yao, and P. Suganthan, Benchmark functions for the CEC' 2008 special session and competition on large scale global optimization, 2007.

J. Derrac, S. García, and D. Molina, A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms, Swarm & Evolutionary Computation, vol.1, issue.1, pp.3-18, 2011.

D. Wolfe and M. Hollander, Nonparametric Statistical Methods Robust nonparametric statistical methods. Arnold, pp.189-211, 1998.

C. Coello, Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art, Computer Methods in Applied Mechanics and Engineering, vol.191, issue.11, pp.1245-1287, 2002.

A. D. Belegundu, . Arora, and S. Jasbir, A Study of Mathematical Programming Methods for Structural Optimization, International Journal for Numerical Methods in Engineering, vol.21, issue.9, pp.1601-1623, 1985.

E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi, GSA: A Gravitational Search Algorithm. Intelligent Information Management, vol.4, issue.6, pp.390-395, 2012.

Q. He and L. Wang, An effective co-evolutionary particle swarm optimization for constrained engineering design problems, Engineering Applications of Artificial Intelligence, vol.20, issue.1, pp.89-99, 2007.

C. Coello, Use of a self-adaptive penalty approach for engineering optimization problems, 2000.