Algorithm 1 Pseudocode of NMRA

Input:Define objective functionf(NMR), NMR = (NMR1, NMR2, . . ., NMRD)

Output:Identify current best solution$\mathit{d}$;

Initialization:Initialize NMRs: n, breedersB:n/5, workersW:B−n

Describe breeding probability: bp

while iterations < $\mathit{i}{\mathit{t}}_{\mathit{m}\mathit{a}\mathit{x}}$

for i = 1: w

${\mathit{w}}_{\mathit{i}}^{\mathit{t}+1}={\mathit{w}}_{\mathit{i}}^{\mathit{t}}+\mathit{\lambda }\left({\mathit{w}}_{\mathit{j}}^{\mathit{t}}-{\mathit{w}}_{\mathit{k}}^{\mathit{t}}\right)$

evaluate${\mathit{w}}_{\mathit{i}}^{\mathit{t}+1}$

end for

for i = 1: B

if rand >bp

${\mathit{b}}_{\mathit{i}}^{\mathit{t}+1}=\left(1-\lambda \right){\mathit{b}}_{\mathit{i}}^{\mathit{t}}+\lambda \left(\mathit{d}-{\mathit{b}}_{\mathit{i}}^{\mathit{t}}\right)$

end if

evaluate${\mathit{b}}_{\mathit{i}}^{\mathit{t}+1}$

end for

combine the updated breeder and worker population

estimate the NMRs

update the overall best d

update iteration count

end while

update final best$\mathit{d}$

end