为了更为直观的反应算法的寻优特点，图2给出了CCGOA算法与其他算法对

For optimization of the characteristics of the reaction more intuitive algorithm, Figure 2 shows a comparison of convergence curve F1 ~ F12 function CCGOA algorithm and other algorithms. As can be seen from Figure 2 F1 ~ F12 function corresponding to the curve, in addition to the function F9, CCGOA remaining 11 has a function of good searching ability, convergence rate, optimization, much better than CGOA, GOA, PSO, MFO , CCS, OBLGOA and SCA algorithm, for most functions, CCGOA long iterative algorithm several times to find the optimal theoretical value, especially for the function F7, seven other algorithms into a local optimum, we converge to approaching 0.01 local minima, CCGOA after several iterations to find the theoretical optimal value. Can further be seen from Figure 3, in addition to the function F9, CCGOA algorithm has a good robustness, mean its optimal value, median, seven kinds of algorithms are better than most other value, reaching the target more nearly ideal value 0.

In order to find the superior characteristics of the more intuitive reaction algorithm, Figure 2 shows the convergence curve of the CCGOA algorithm with the F1 to F12 function with other algorithms. From the curve of the F1-F12 function in Figure 2, it can be seen that, in addition to the function F9, CCGOA has good ability to find good in the remaining 11 functions, and its convergence speed and optimization accuracy are significantly better than CGOA, GOA, PSO, MFO, CCS, OBLA and SCA algorithms, for most functions, CCGOA algorithm as long as several iterations can find the theoretical optimal value, especially for the function F7, the other 7 kinds of algorithms are caught in the local optimal, all converge towards the local minimum value of 0.01, CCGOA after several iterations to find the theoretical optimal value. From Figure 3 can be further seen, in addition to the function F9, CCGOA algorithm has a good robustness, its optimal value of the mean, median, the most value are better than the other 7 algorithms, reached the target ideal value more close to 0.

In order to have a more intuitive response algorithm, figure 2 shows the convergence curve of ccgoa algorithm compared with other algorithms for F1 ~ F12 functions. It can be seen from the curve corresponding to F1-F12 functions in Figure 2 that except for function F9, ccgoa has good optimization ability in the remaining 11 functions, and its convergence speed and optimization accuracy are significantly better than CGOA, Goa, PSO, MFO, CCS, oblgo and SCA algorithms. For most functions, ccgoa algorithm can find the theoretical optimal value as long as it iterates several times, especially for function F7, the other seven algorithms fall into the trap The partial optimum converges to the local minimum of 0.01. After several iterations, ccgoa finds the theoretical optimum. It can be further seen from Figure 3 that in addition to function F9, ccgoa algorithm has good robustness, and its optimal value is better than the other seven algorithms in mean value, median value and maximum value, reaching the target ideal value closer to 0.<br>