Triple-Band Single-Layer Rectenna for Outdoor RF Energy Harvesting Applications

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. 2021 May 16;21(10):3460. doi: 10.3390/s21103460

Algorithm 1 Pseudo-code of the Moth Search Algorithm.

1:
Define the population number of moths $N P o p$ , the sub-populations $N P o p^{A}$ and $N P o p^{B}$ , the maximum number of generations $M a x G e n$ , and the number of decision variables $M a x V a r$
2:
Define the maximum step size of random path in Lévy distribution $s t e p_{\max}$ = 1.0
3:
Set g = 1
4:
for (g = 1; $g + +$ ; $g \leq M a x G e n$ ) do
5:
Initialize the position $m_{i, j}^{g}$ , the best position $m_{best, j}^{g}$ and the fitness value $O F (m_{i, j}^{g})$ of each i-th moth in every j-th decision variable at g-th generation
6:
——————————Lévy flight——————————
7:
Set $i A$ = 1 and $i n d e x$ = 1.5
8:
for ( $i A$ = 1; $i A + +$ ; $i A \leq N P o p^{A}$ ) do
9:
Compute the scale factor $f_{sc}$ using (3)
10:
Compute the Lévy distribution parameter value using (2)
11:
Compute the position of each moth using (1)
12:
end for
13:
——————————Straight flight——————————
14:
Set $i B$ = 1
15:
for ( $i B$ = 1; $i B + +$ ; $i B \leq N P o p^{B}$ ) do
16:
Set j = 1
17:
for (j = 1; $j + +$ ; $j \leq M a x V a r$ ) do
18:
if ( $r a n d \geq 0.5$ ) then
19:
Compute the position of each moth using (4a)
20:
else
21:
Compute the acceleration factor using (5)
22:
Compute the position of each moth using (4b)
23:
end if
24:
end for
25:
end for
26:
Compute the updated fitness value $O F (m_{i, j}^{g})$ for each moth
27:
Update the moth with the best position $m_{best, j}^{g}$ based on the fitness value
28:
end for