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. 2020 Jan 8;20(2):356. doi: 10.3390/s20020356

Algorithm 2 Genetic Algorithm (GA)

Input:

Maximum number of generations (

M a x G e n

).

Population size (

P o p S i z e

).

Lower and upper bound variables (

v a r_{m i n}, v a r_{m a x}

).

Output:

Best value of all chromosomes (

G l o b a l B e s t r s s i

).

1:
for i=1: $P o p S i z e$ do
2:
$p o s_{i} = r a n d (v a r_{m i n}, v a r_{m a x})$
3:
$r s s i_{i} = p a t h l o s s (p o s_{i})$
4:
$B e s t p o s_{i} = p o s_{i}$
5:
end for
6:
for t=1: $M a x G e n$ do
7:
for i=1: $P o p S i z e$ do
8:
$S e l e c t P a r e n t s$
9:
$C r o s s o v e r$
10:
$M u t a t i o n$
11:
$p o s_{i} = p o s_{i + 1}$
12:
$B e s t p o s_{i} = p o s_{i}$
13:
$B e s t r s s i_{i} = r s s i_{i}$
14:
$G l o b a l B e s t r s s i = B e s t r s s i_{i}$
15:
end for
16:
end for