An Improved Grey Wolf Optimization Algorithm with Variable Weights

Table 6

MLITs and statistical results for F1.

dim	Algorithm	Best	Worst	Mean	t-test (α = 0.05)	Std. deviation	Number
2	VW-GWO	6	12	9.90	1.7180e − 193	1.0493	100
	Std. GWO	7	13	10.38	1.8380e − 22	1.2291	100
	PSO	48	1093	357.97	3.2203e − 22	205.3043	100
	BA	29	59	41.00	1.3405e − 101	5.8517	100
10	VW-GWO	53	66	59.97	4.1940e − 177	2.7614	100
	Std. GWO	74	89	80.40	1.9792e − 80	2.7614	100
	PSO	5713	11510	9279.22	2.9716e − 76	1300.8485	88
	BA	6919	97794	44999.04	7.5232e − 26	25133.3096	78
30	VW-GWO	55	67	59.85	1.2568e − 122	2.4345	100
	Std. GWO	71	86	80.07	2.6197e − 79	3.3492	100
	PSO	5549	12262	9314.78	9.6390e − 83	1316.3384	96
	BA	7238	92997	44189.16	5.2685e − 26	24831.7443	79