# A Compact Cat Swarm Optimization Algorithm Based on Small Sample Probability Model
## 4 Experimental Results and Analysis
### Comparison between the Corresponding Population-Based Algorithms and SSPCCSO  
In addition to the comparison with memory saving algorithms, another group of comparisons between memory-saving and non-memory-saving algorithms are also used to test the performance of the algorithms; The comparison between sspccso, CSO, PSO and de will be arranged in this group of experiments. Table 4 presents the comparison results of the 47 test functions. SSPCCSO did better in 10 benchmarks, even when only one cat was employed. This status also happens in comparison between DE [23], cDE [2], PSO [24] and cPSO [4]. Obviously, Compared with population-based bio-inspired algorithms, the search ability of a single individual in SPCCSO is limited, and there is no large population collective cooperative search. However, the performance of SPCCSO still exceeds other algorithms. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Benchmark** & **DE** & **PSO** & **W** & **CSO** & **W** & **SSPCCSO** \\ \hline fu1 & \(8.269\times 10^{1}\pm\) & \(1.095\times 10^{4}\pm\) & \(-\) & \(\mathbf{0.000\times 10^{0}\pm}\) & \(-\) & \(6.170\times 10^{-3}\pm\) \\  & \(1.90\times 10^{1}\) & \(2.30\times 10^{3}\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(\mathbf{1.05\times 10^{-3}}\) \\ fu2 & \(3.063\times 10^{4}\pm\) & \(4.232\times 10^{4}\pm\) & \(+\) & \(\mathbf{0.000\times 10^{0}\pm}\) & \(-\) & \(3.625\times 10^{2}\pm\) \\  & \(3.70\times 10^{3}\) & \(1.84\times 10^{3}\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(-\) & \(7.02\times 10^{2}\) \\ fu3 & \(\mathbf{2.715\times 10^{0}\pm}\) & \(1.103\times 10^{9}\pm\) & \(+\) & \(2.890\times 10^{1}\pm\) & \(-\) & \(5.776\times 10^{-1}\pm\) \\  & \(\mathbf{1.11\times 10^{6}}\) & \(5.07\times 10^{8}\) & \(+\) & \(1.394\times 10^{-2}\) & \(-\) & \(7.01\times 10^{0}\) \\ fu4 & \(4.072\times 10^{1}\pm\) & \(1.639\times 10^{1}\pm\) & \(+\) & \(\mathbf{0.001\times 10^{0}\pm}\) & \(-\) & \(5.574\times 10^{-1}\pm\) \\  & \(1.98\times 10^{-1}\) & \(1.21\times 10^{0}\) & \(+\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(-\) & \(3.07\times 10^{-2}\) \\ fu5 & \(7.195\times 10^{1}\pm\) & \(\mathbf{0.001\times 10^{0}\pm}\) & \(-\) & \(\mathbf{0.001\times 10^{0}\pm}\) & \(-\) & \(1.613\times 10^{-2}\pm\) \\  & \(9.73\times 10^{0}\) & \(\mathbf{0.001\times 10^{0}\pm}\) & \(-\) & \(\mathbf{0.01\times 10^{0}\pm}\) & \(-\) & \(2.37\times 10^{-3}\) \\ fu6 & \(2.151\times 10^{2}\pm\) & \(2.887\times 10^{2}\pm\) & \(+\) & \(\mathbf{0.001\times 10^{0}\pm}\) & \(-\) & \(2.399\times 10^{-2}\pm\) \\  & \(9.08\times 10^{0}\) & \(3.28\times 10^{1}\) & \(+\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(-\) & \(4.09\times 10^{-3}\) \\ fu7 & \(2.408\times 10^{5}\pm\) & \(1.321\times 10^{5}\pm\) & \(+\) & \(\mathbf{2.990\times 10^{2}\pm}\) & \(\mathbf{2.991\times 10^{2}\pm}\) & \(-\) & \(2.991\times 10^{2}\pm\) \\  & \(4.96\times 10^{4}\) & \(1.03\times 10^{4}\) & \(+\) & \(\mathbf{0.00\times 10^{0}\pm}\) & \(-\) & \(1.75\times 10^{-1}\) \\ fu8 & \(6.328\times 10^{3}\pm\) & \(6.677\times 10^{3}\pm\) & \(-\) & \(3.161\times 10^{3}\pm\) & \(-\) & \(\mathbf{1.248\times 10^{0}\pm}\) \\  & \(2.36\times 10^{2}\) & \(6.44\times 10^{2}\) & \(-\) & \(9.76\times 10^{2}\) & \(-\) & \(\mathbf{1.90\times 10^{0}\pm}\) \\ fu9 & \(1.633\times 10^{4}\pm\) & \(1.305\times 10^{4}\pm\) & \(+\) & \(1.344\times 10^{4}\pm\) & \(+\) & \(1.111\times 10^{5}\pm\) \\  & \(1.13\times 10^{3}\) & \(3.17\times 10^{3}\) & \(+\) & \(1.74\times 10^{3}\) & \(+\) & \(5.29\times 10^{4}\) \\ fu10 & \(\mathbf{8.508\times 10^{5}\pm}\) & \(9.716\times 10^{5}\pm\) & \(-\) & \(3.222\times 10^{6}\pm\) & \(+\) & \(9.390\times 10^{5}\pm\) \\  & \(\mathbf{9.24\times 10^{4}}\) & \(1.57\times 10^{5}\) & \(-\) & \(1.68\times 10^{5}\) & \(+\) & \(1.13\times 10^{4}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison among SSPCCSO, CSO, PSO and DE.