Genetic Algorithm for Combinatorial Path Planning: The Subtour Problem

Table 5

Comparison of the proposed method with benchmarked solutions of the traveling salesman problem. Results are averaged over 100 simulations. Rounded distances are used.

Problem TSPLIB	Number of targets	Optimal tour	Genetic algorithm error
		Length	Minimum	Mean	Maximum	Std
Berlin52	52	7542	0%	0%	0%	0
Eil76	76	538	0%	0.02%	1.4%	0.8
KroA100	100	21282	0%	0%	0%	0
lin105	105	14379	0%	0%	0%	0
ch130	130	6110	0%	0.2%	0.9%	15.9
a280	280	2579	0%	0.2%	1%	8.5
pcb442	442	50778	0.3%	0.9%	1.5%	148.6
att532	532	86729	0.4%	1.1%	2%	340.07