Algorithm 3 Pseudocode of DBOA.

1:                  Initialization part.

2: Determine parameters of BOA algorithm. N—number of butterfly in population, n—dimension, c—sensor modality and a, $\xi$, p parameters.

3: Random generate starting population $\{{\mathbf{x}}^1,{\mathbf{x}}^2,\dots ,{\mathbf{x}}^N\}$.

4: Calculate the value of the fitness function F (hence intensity of the stimulus $I=F$) for each butterfly ${\mathbf{x}}^k(k=1,2,\dots ,N)$ in population.

Iterative part.

for $\mathrm{iteration}i=1,2,\dots ,I$ do

for $k=1,2,\dots ,N$ do

Calculate value of fragnance for ${\mathbf{x}}^k$ with the use of Equation (13).

5:    end for

Set the best agent ${\mathbf{x}}_{best}$ among the butterflies.

for $k=1,2,\dots ,N$ do

Set a random number r from range $[0,1]$.

if $r<p$ then

10:      Convert solution ${\mathbf{x}}_k^t$ in accordance with the Equation (14).

else

Convert solution ${\mathbf{x}}_k^t$ in accordance with the Equation (15).

end if

end for

15:  Change value of the parameter a.

Adopt the LSAM algorithm to convert the agents population with mutation rate $\xi$.

end for

return ${\mathbf{x}}^{best}$.