A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

Table 8

Optimal objective function values of two algorithms (yuan).

Instance name	Algorithm	Mean	Standard deviation	Coefficient of variation	Significance test
					value	value (Sig. 2-tailed)
Perl; 183 – 12 × 2	PPGASA	27274.15	3072.70	0.1127	−15.71	0.000
	GA	59644.00	20373.95	0.3416
Gaskell; 67 – 22 × 5	PPGASA	176597.12	51842.11	0.2936	−2.069	0.040
	GA	193606.40	63820.20	0.3296
Gaskell; 67 – 36 × 5	PPGASA	1532353.00	240454.91	0.1569	−24.268	0.000
	GA	3266300.00	672809.81	0.2060
Perl; 183 – 55 × 15	PPGASA	4368430.00	336908.31	0.0771	−3.877	0.000
	GA	4571132.00	399811.55	0.0874
Christofides; 69 − 75 × 10	PPGASA	5653803.00	481169.53	0.0851	−2.113	0.036
	GA	58256800.00	655839.90	0.0113
Perl; 183 – 85 × 7	PPGASA	6095438.00	219212.14	0.0360	−3.388	0.001
	GA	6221775.00	301680.88	0.0485
Christofides; 69 – 100 × 10	PPGASA	6848350.00	617689.91	0.0902	−3.391	0.001
	GA	7179759.00	757338.00	0.1055