Research Article
A Modified Sine-Cosine Algorithm Based on Neighborhood Search and Greedy Levy Mutation
Table 5
Test statistical results of functions
.
| | Benchmark function | PSO | DE | BA | TLBO | GWO | CSA | MSCA |
| | Best | 0.99800384 | 0.99800384 | 0.99800384 | 0.99800384 | 0.99800384 | 0.99800384 | 0.998003838 | | Mean | 1.29561904 | 0.99800384 | 3.36874514 | 0.99800384 | 0.99800384 | 0.99800387 | 0.998003838 | | Worst | 2.98210516 | 0.99800384 | 6.90333569 | 0.99800384 | 0.99800384 | 0.99800414 | 0.998003838 | | Std | 0.72687065 | 0 | 2.26483904 | 0 | 0 | 0.00000007 | 0 |
| | Best | 0.00030752 | 0.00030749 | 0.00030749 | 0.00030749 | 0.00030749 | 0.00031054 | 0.00030748598 | | Mean | 0.00347700 | 0.00030749 | 0.00030749 | 0.000307486 | 0.00049062 | 0.00041204 | 0.00030748598 | | Worst | 0.02036334 | 0.00030749 | 0.00030749 | 0.000307486 | 0.00122317 | 0.00126659 | 0.00030748598 | | Std | 0.00694358 | 0 | 0 | 1.50786E-19 | 0.00040951 | 0.00029067 | 0 |
| | Best | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162842 | -1.03162845 | | Mean | -1.03162842 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162684 | -1.03162845 | | Worst | -1.03162833 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162845 | -1.03162424 | -1.03162845 | | Std | 0.00000004 | 0 | 0 | 2.27813E-16 | 0 | 0.00000122 | 0 |
| | Best | 0.39788737 | 0.397887358 | 0.39788736 | 0.397887358 | 0.39788736 | 0.39788838 | 0.397887358 | | Mean | 0.39788774 | 0.397887358 | 0.39788736 | 0.397887358 | 0.39789181 | 0.39799018 | 0.397887358 | | Worst | 0.39788882 | 0.397887358 | 0.39788736 | 0.397887358 | 0.39790961 | 0.39837908 | 0.397887358 | | Std | 0.00000041 | 0 | 0 | 0 | 0.00000995 | 0.00013970 | 0 |
| | Best | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000000 | | Mean | 3.00000553 | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000006 | 3.00000003 | 3.00000000 | | Worst | 3.00002104 | 3.00000000 | 3.00000000 | 3.00000000 | 3.00000010 | 3.00000008 | 3.00000000 | | Std | 0.00000656 | 0 | 0 | 7.62408E-16 | 0.00000004 | 0.00000003 | 0 |
| | Best | -3.86278215 | -3.86278215 | -3.86278214 | -3.86278215 | -3.86278215 | -3.86226093 | -3.86278215 | | Mean | -3.86278211 | -3.86278215 | -3.86278214 | -3.86278215 | -3.86278203 | -3.85557758 | -3.86278215 | | Worst | -3.86278193 | -3.86278215 | -3.86278213 | -3.86278215 | -3.86278159 | -3.85462395 | -3.86278215 | | Std | 0.00000005 | 0 | 0.00000001 | 2.27813E-15 | 0.00000024 | 0.00227718 | 0 |
| | Best | -3.32199431 | -3.32199517 | -3.32199432 | -3.32199517 | -3.32199514 | -3.16816134 | -3.32199517 | | Mean | -3.23885032 | -3.32199517 | -3.27443705 | -3.31604271 | -3.24969715 | -3.02251139 | -3.32199517 | | Worst | -3.08390118 | -3.32199517 | -3.20310148 | -3.20310205 | -3.19844899 | -2.62970467 | -3.32199517 | | Std | 0.07507732 | 0 | 0.06512014 | 2.6583E-02 | 0.06602515 | 0.14476696 | 0 |
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