Table 1.
The leadership hierarchy of the grey wolves pack.
Fig 1.
An example of leaving the promising region for the less promising one in 1-D case.
Fig 2.
Exploration versus exploitation periods depending on the parameter a in GWO [23].
Fig 3.
The shrinking of the random walk limits as per the parameter I [25].
Fig 4.
The possible positions of a given moth with respect to the corresponding flame [26].
Fig 5.
The Singer exploration rate versus the native exploration used as a part of GWO, ALO, and MFO.
Fig 6.
The Sinusoidal exploration rate versus the native exploration used as a part of GWO, ALO, and MFO.
Table 2.
Description of the data sets used in the study.
Table 3.
Parameter setting for experiments.
Fig 7.
Mean fitness values for the ALO versus CALO using the Singer function.
Fig 8.
Mean fitness values for the ALO versus CALO using the Sinusoidal function.
Fig 9.
Mean fitness values for the GWO versus CGWO using the Singer function.
Fig 10.
Mean fitness values for the GWO versus CGWO using the Sinusoidal function.
Fig 11.
Mean fitness values for the MFO versus CMFO using the Singer function.
Fig 12.
Mean fitness values for the MFO versus CMFO using the Sinusoidal function.
Fig 13.
Possible positions for a moth using the different values for the a parameter.
Fig 14.
Average classification performance for the ALO versus CALO using the Singer function.
Fig 15.
Average classification performance for the ALO versus CALO using the Sinusoidal function.
Fig 16.
Average classification performance for the GWO versus CGWO using the Singer function.
Fig 17.
Average classification performance for the GWO versus CGWO using the Sinusoidal function.
Fig 18.
Average classification performance for the MFO versus CMFO using the Singer function.
Fig 19.
Average classification performance for the MFO versus CMFO using the Sinusoidal function.
Fig 20.
Standard deviation (std) of the obtained optimal fitness values for ALO versus CALO using the Singer and Sinusoidal functions.
Fig 21.
Standard deviation (std) of the obtained optimal fitness values for GWO versus CGWO using the Singer and Sinusoidal functions.
Fig 22.
Standard deviation (std) of the obtained optimal fitness values for MFO versus CMFO using the Singer and Sinusoidal functions.
Table 4.
Average selection features size for the chaotic and native ALO over all the data sets.
Table 5.
Average selection features size for the chaotic and native GWO over all the data sets.
Table 6.
Average selection features size for the chaotic and native MFO over all the data sets.
Table 7.
Significance tests for optimizers pairs.
Fig 23.
Fitness sum over all the used data sets for CALO versus ALO and PSO at a different setting of α.
Fig 24.
Fitness sum over all the used data sets for CGWO versus GWO and PSO at a different setting of α.
Fig 25.
Fitness sum over all the used data sets for CMFO versus MFO and PSO at a different setting of α.