| For gn (gene) = 1 : 30 |
| Initialize the population para with host nests (solutions) with |
| dimension = 3 that is . |
| For : 10 |
| Calculate fob (fitness value) for all 10 solutions using RNN and FPA; |
| If () |
| Break; |
| End if; |
| End for; |
| If (minimum (fob) ) |
| For : max iteration (100) |
| Randomly select a cuckoo (th) avoid current best; |
| Randomly generate another nest (th) keeping current best nests by Lévy flights; |
| If () |
| is replaced by the news solution; |
| End if; |
| If () |
| Break; |
| End; |
| Discard the worse nests with a fractional probability (); |
| Keep the highest quality nest that is best solution with best fitness value; |
| Rank the available solutions and locate the current best; |
| End for; |
| End if; |
| End for; |
| Post-processing and visualization of GRN; |
| Function fob (para, gn) |
| Initialize a rnnpara population of nf (30) with dimension df (5) pollen randomly with a switch probability |
| Find the fitness fun for all solutions and best pollen among them |
| For (tf < MaxGeneration (2000)) |
| For : nf |
| If , |
| Draw (df-dimensional) step vector L which obeys a Lévy distribution |
| Global pollination via equation (4) |
| Else |
| Draw from a uniform distribution in |
| Randomly choose jf and kf among all the solutions |
| Do local pollination via equation (5) |
| End if |
| Evaluate fitness fun of new solutions of pollens |
| If new solutions are better |
| Update them in the population |
| End if |
| End for |
| Find store the best fitness of current iteration |
| If ((bestfitness (tf) <) (() && ((bestfitness () − bestfitness (tf)) < ))) |
| Break |
| End if |
| End for |
| Return bestfitness |
| End fob |
| Function fun (rnnpara, para, gn) |
| Define (5) times series data with (50) sample point |
| Calculate the gene expression value of next time instance using equation (1) |
| Determine the squared error using equation (7) |
| Return error |
| End fun |
