A Systematic Review of Optimization Algorithms for Structural Health Monitoring and Optimal Sensor Placement

. 2023 Mar 20;23(6):3293. doi: 10.3390/s23063293

Algorithm 3 Pseudo-code for PSO Algorithm.

1:
Determine objective function $f (x)$ .
2:
Initialize parameters $c 1$ , $c 2$ , $w_{\max}$ , $w_{\min}$ , and population size $n P o p$ .
3:
Evaluate the fitness of each particle and set all initial positions as $P_{best, x}$ .
4:
Generate an initial population of particles.
5:
while $t < M a x G e n e r a t i o n$ do
6:
Select the $G_{best}$ particle in the swarm, which has the minimum fitness value
7:
for $i = 1 : n P o p$ do
8:
Calculate the velocity of particle $x_{i}$ .
9:
Update the position of particle $x_{i}$ .
10:
end for
11:
for $i = 1 : n P o p$ do
12:
Evaluate the fitness of updated particle $x_{i}$ .
13:
if $f (x_{i}) < f (P_{best, x})$ then
14:
Set current position as $P_{best, x}$ .
15:
end if
16:
end for
17:
Find the best particle
18:
end while