Global Optimization for Solving Linear Multiplicative Programming Based on a New Linearization Method

Table 2

Comparison results of Algorithms and for Examples 1–10.

Example; ()	Methods	Time (s)	Iter	Optimal solution	Optimal value
1 (min); ()	Algorithm	0.062	1	(2.0, 8.0)	10
	Algorithm	0.062	1	(2.0, 8.0)	10
2 (min); ()	Algorithm	0.086	1	(0.0, 4.0)	3
	Algorithm	0.086	1	(0.0, 4.0)	3
3 (min); ()	Algorithm	0.093	1	(1.3148, 0.1396, 0.0, 0.4233)	0.8902
	Algorithm	0.093	1	(1.3148, 0.1396, 0.0, 0.4233)	0.8902
4 (min); ()	Algorithm	0.0842	1	(0.0, 4.0)	3
	Algorithm	0.0842	1	(0.0, 4.0)	3
5 (min); ()	Algorithm	0.0150	1	(1.0, 3.0)	−13
	Algorithm	0.0150	1	(1.0, 3.0)	−13
6 (min); ()	Algorithm	0.0160	1	(1.0, 4.0)	−22
	Algorithm	0.0160	1	(1.0, 4.0)	−22
7 (min); ()	Algorithm	1.5930	34	(5.5556, 1.7778, 2.6667)	−112.7531
	Algorithm	1.9091	58	(5.5556, 1.7778, 2.6667)	−112.7531
8 (max); ()	Algorithm	0.5	16	(0.75, 0.75)	−38.8750
	Algorithm	1.6425	64	(0.75, 0.75)	−38.8750
9 (min); ()	Algorithm	0.659	23	(1.5480, 2.4152)	−16.2893
	Algorithm	1.7235	39	(1.5480, 2.4152)	−16.2893
10 (min); ()	Algorithm	0.7662	27	(1.5568, 0.7545)	10.6753
	Algorithm	1.4862	68	(1.5480, 2.4152)	10.6753