Research Article

Improved Gradient-Based Optimizer for Modelling Thermal and Hydropower Plants

Table 2

Results of multimodal benchmark functions.

FunctionIGBOGBOHPOWOASDOGWO

F8Best−1909.05−1872.79−1795.63−1909.05−1655−1495.31
Mean−1761.77−1743.83−1675.9−1786.9−1312.83−1245.57
Median−1751.43−1732.31−1684.22−1907.06−1385.86−1224.18
Worst−1650.19−1659.76−1452.47−1632.06−598.802−1123.85
STD81.0865758.413573.47505138.0759294.008104.0153

F9Best00004.33E − 301.062467
Mean0001.14E − 141.75E − 229.801018
Median00004.17E − 259.824713
Worst0001.14E − 133.02E − 2124.96968
STD0002.97E − 146.75E − 225.565812

F10Best8.88E − 168.88E − 168.88E − 164.44E − 158.88E − 1620.76487
Mean8.88E − 168.88E − 168.88E − 161.33E − 148.88E − 1620.92344
Median8.88E − 168.88E − 168.88E − 161.15E − 148.88E − 1620.94465
Worst8.88E − 168.88E − 168.88E − 163.29E − 148.88E − 1621.06309
STD0008.11E − 1500.083433

F11Best000006.56E − 13
Mean0000.02183200.009891
Median000004.55E − 12
Worst0000.2662600.055407
STD0000.06897300.015766

F12Best2.76E − 095.1E − 065.47E − 090.0060520.0011520.006066
Mean1.13E − 083.6E − 050.0051830.0222390.234670.026151
Median1.02E − 082.19E − 052.8E − 080.0155290.0678050.023474
Worst2.16E − 080.0002170.1036690.0879471.4928210.047176
STD5.16E − 094.68E − 050.0231810.0187740.3520630.013414

F13Best1.09E − 070.0003699.49E − 070.4002810.0462160.09955
Mean0.1078920.0140060.1115060.6875221.8675520.613832
Median0.0109880.0083660.1105890.5980541.9342460.609981
Worst0.6003170.0523190.2964931.3213522.9999241.044
STD0.1840080.0168890.1018890.2485230.9612840.280029
The best obtained values are in bold.