Research Article

Lens Learning Sparrow Search Algorithm

Algorithm 1

The framework of the LLSSA.
Input
M: the maximum iterations
PD: the number of producers
SD: the number of sparrows who perceive the danger
R2: the alarm value
N: the number of sparrows
λ: attenuation parameter
Initialize a population of N sparrows and define its relevant
Output: ,
Initialize the population according to equation (5)
t = 1;
While (t < M)
Rank the fitness values and find the current best individual and the current worst individual.
R2 = rand(1)
For i = 1: PD
Using equation (7) and equation (8) update the finder's location;
End for
For i = (PD + 1) : N
Using equation (13) update the follower's location;
End for
For l = 1 : SD
Updating the position of a sparrow individual who is aware of danger according to equation (3);
End for
Perform simulated annealing
Get the current new location;
If the new location is better than before, update it.
t = t + 1
End while
Return: ,