Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation

Table 4

The comparison results of the three algorithms on the 50-dimensional benchmark functions.

Function	Algorithm	Best	Worst	Mean	Std
	MBO	0.1477	398.2232	209.3775	139.9068
	GCMBO	1.8428e-13	1.0670e-08	1.1156e-09	2.1500e-09
	OPMBO	1.5567e-10	2.7548e-08	8.8554e-09	7.5075e-09
	MBO	0.0034	415.5476	153.3220	142.7727
	GCMBO	1.9171e-07	133.2460	19.7500	29.8177
	OPMBO	1.2181e-28	6.6022e-23	9.4507e-24	1.6826e-23
	MBO	0.0010	1.6716e+05	7.1776e+04	5.1240e+04
	GCMBO	2.3034e+03	7.4799e+04	2.8123e+04	1.7575e+04
	OPMBO	9.7152e-10	4.7017e+04	1.9873e+03	8.6490e+03
	MBO	0.0071	90.5485	35.3305	26.7642
	GCMBO	0.0299	85.3000	33.9794	21.5405
	OPMBO	1.4047e-06	22.7838	4.0685	6.5366
	MBO	0.1832	227.1000	130.7104	79.0919
	GCMBO	0	110.2839	23.6658	35.6746
	OPMBO	1.0957e-06	7.7733e-05	2.7397e-05	1.6504e-05
	MBO	0	132209	5.1815e+04	5.1859e+04
	GCMBO	0	12346	1696	2.9548e+03
	OPMBO	0	0	0	0
	MBO	1.3455e-04	1.8360e+04	5.9326e+03	6.2480e+03
	GCMBO	3.3925e-09	1.4881e+03	243.2459	353.8553
	OPMBO	1.2070e-05	306.7838	46.0623	53.5043
	MBO	3.4589e-11	1.1141e+09	2.4720e+08	4.0804e+08
	GCMBO	2.0184e-17	5.4740e+07	3.2179e+06	1.0925e+07
	OPMBO	4.5879e-19	9.7859e-13	1.1863e-13	2.1688e-13
	MBO	6.5719e-10	1.9497e+09	3.6131e+08	6.4416e+08
	GCMBO	9.8724e-16	1.4513e+08	1.0977e+07	3.1121e+07
	OPMBO	1.2994e-16	9.2119e-12	1.9405e-12	2.1819e-12
	MBO	3.0017	20.7867	15.9858	6.1167
	GCMBO	6.6066e-07	19.8083	1.9658	4.6606
	OPMBO	1.0861e-06	9.8438e-05	4.0379e-05	2.2417e-05
	MBO	2.4511e+03	1.6770e+04	1.0050e+04	4.1486e+03
	GCMBO	6.3638e-04	8.0438e+03	4.2775e+03	2.7433e+03
	OPMBO	6.3638e-04	6.0967e+03	970.1854	2.2072e+03
	MBO	26.7258	851.3496	489.7041	275.3819
	GCMBO	1.9838e-10	98.6456	17.8949	31.4580
	OPMBO	7.4206e-09	124.9711	4.1657	22.8165