A Novel Hybrid Algorithm Based on Grey Wolf Optimizer and Fireworks Algorithm

. 2020 Apr 10;20(7):2147. doi: 10.3390/s20072147

Algorithm 3 Pseudo Code of FWGWO

\begin{array}{l} 1 . Initialize the wolf population X_{i} (i = 1, 2, \dots, n) \\ 2 . Initialize a, A, k, t and C \\ 3 . Calculate the fitness of each search agent \\ 4 . X_{α} = the best search agent \\ 5 . X_{β} = the \sec ond best search agent \\ 6 . X_{δ} = the third best search agent \\ 7 . while (t < Max number of iterations) \\ 8 . for each search agent \\ 9 . Update the position of the current search agent by equation (7) \\ 10 . end for \\ 11 . Update a, A, and C \\ 12 . Calculate the fitness of all search agents \\ 13 . Update X_{α}, X_{β}, and X_{δ} \\ 14 . if X_{α} changed then \\ 15 . Update the adaptive balance coefficient (p) by equation (16) \\ 16 . end if \\ 17 . if k > = T and r a n d () > p then \\ 18 . for e a c h s e a r c h a g e n t x_{i} do \\ 19 . Generate explosion sparks \\ 20 . end for \\ 21 . Generate m Gaussian spark for the search agents \\ 22 . Selec new search agents by equation (15) \\ 23 . t = t + 1 \\ 24 . k = 0 \\ 25 . end if \\ 26 . k = k + 1 t = t + 1 \\ 27 . end while \\ 28 . return X_{α} \end{array}