Research on the Distribution of Emergency Supplies during the COVID-19 Epidemic

Table 3

Comparison of solution results of 9 optimization algorithms.

Source	Algorithm	Average path length	Optimal path length	Optimal number of vehicles	Optimal distribution solution
Jian et al. [38]	Simple genetic algorithm	1611.474	1463.823	7	0-17-8-16-0, 0-4-12-19-13-0, 0-18-3-2-0, 0-1-11-15-0, 0-6-9-0, 0-10-20-0, and 0-7-5-14-0
	Simulated annealing algorithm based on or-opt	1219.931	1190.181	6	0-7-3-14-0, 0-10-17-2-0. 0-18-5-11-0, 0-12-19-20-13-6-0, 0-15-4-9-0, and 0-1-8-16-0
	Hybrid genetic algorithm	1159.703	1159.229	6	0-10-20-17-2-0, 0-18-3-11-0, 0-15-4-9-0, 0-7-5-14-0, 0-1-16-8-0, and 0-12-19-6-13-0
Yin and Zhang [28]	Basic bat algorithm	1404.4	1290.6	8	0-18-3-4-0, 0-6-13-0, 0-8-16-0, 0-1-14-0, 0-10-2-17-0, 0-9-15-0, 0-12-19-20-0, and 0-7-11-5-0
	Elite genetic hybrid bat algorithm	1170.0	1136.6	7	0-10-13-20-0, 0-8-16-0, 0-12-19-6-0, 0-7-15-4-0, 0-1-2-17-0, 0-18-5-9-0, and 0-3-11-14-0
	Multipoint recombination elite hybrid bat algorithm	1162.3	1105.9	6	0-3-11-14-0, 0-1-16-0, 0-18-7-5-15-0, 0-20-13-10-19-0, 0-12-4-9-0, and 0-8-2-17-6-0
	Single-point recombination elite hybrid bat algorithm	1163.1	1090.2	6	0-4-15-9-0, 0-11-14-3-0, 0-18-7-5-0, 0-12-19-6-13-0, 0-1-16-8-0, and 0-10-20-17-2-0
Chen et al. [36]	Variable neighborhood search algorithm	1020.75	1004.32	6	0-10-20-17-2-0, 0-7-5-14-0, 0-4-15-9-0, 0-18-11-3-0, 0-1-16-8-0, and 0-12-19-6-13-0
This paper	BOSA	1005.01	1004.32	6	0-12-19-6-13-0, 0-4-15-9-0, 0-18-11-3-0, 0-10-20-17-2-0, 0-7-5-14-0, and 0-1-16-8-0