In addition to the above experiments, we compare the CFOA with recently developed state-of-the-art chaotic algorithms. Besides CFOA, we implemented chaotic bat algorithm (CBA), chaotic accelerated particle swarm optimization (CAPSO), chaotic firefly algorithm (CFA), chaotic artificial bee colony algorithm (CABC), and chaotic cuckoo search (CCS). Population size, maximum number of iterations, and specific algorithm parameters Cyclic Pifithrin-α hydrobromide presented in Table 21, while comparison results are given in Table 22. All aforementioned algorithms are implemented and tested in Matlab software under the same initial conditions. The algorithms are tested on 3 unimodal and 3 multimodal functions with global optimum equal to zero. Best chaotic maps are employed for each individual algorithm: Sinusoidal map for CBA and CAPSO [17] and [19], Logistic map for CCS [29], and Gauss map for CABC and CFA [22] and [24]. Results indicate sieve cells the CFOA outperforms all other algorithms in terms of mean final optimization result, except for the F8 and F9 in which the identical result is obtained as with employed CABC. This is an additional proof that the implementation of chaotic component remarkably improves the standard FOA. Finally, Friedman test also confirms the superiority of CFOA (Table 22).
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