Abstract—This work integrates chaotic maps into the recently proposed heuristic algorithm called Biogeography-Based Optimization (BBO) algorithm. The effects of 3 different chaotic maps such as Circle, Sine, and Sinusoidal on improving the performance of BBO are investigated in terms of local optima avoidance and convergence speed. The algorithms are benchmarked on four thirty-dimensional test function such as Sphere, Schwefel, Rasterigin, and Griewank. The results prove that chaotic maps (especially Sine map) are able to improve the performance of BBO.

Index Terms—BBO, chaos theory, chaotic maps, evolutionary algorithm.

S. Saremi is with the University of Queensland, St Lucia, and 4072QLD (e-mail: shahrzad.saremi@ uqconnect.edu.au).
S. Mirjalili is with the Griffith University, 170 Kessels Rd, and Nathan 4111QLD (e-mail: seyedali.mirjalili@griffithuni.edu.au).

Cite:Shahrzad Saremi and Seyedali Mirjalili, "Integrating Chaos to Biogeography-Based Optimization Algorithm," International Journal of Computer and Communication Engineering vol. 2, no. 6, pp. 655-658, 2013.