Biological Flower Pollination Algorithm with Orthogonal Learning Strategy and Catfish Effect Mechanism for Global Optimization Problems

Algorithm 3

The pseudocode of the OCFPA.

Input

 Pollen .

 Objective function of minimization or maximization problems.

 Number of pollen (NP), number of fitness evaluations (FEs).

 Switch probability (), step factor ().

Output

 Global best pollen ().

Begin

 % Initialize the population of pollen randomly.

 For to number of pollen (NP)

  .

  Compute the fitness value and store it.

 End for

 The pollen with the best fitness value is chosen as the current best pollen.

 While (the maximum number of fitness evaluations is not reached)

  Draw a random integer  .

  For to number of pollen (NP)

  If a random number in < switch probability (p)

  % conduct global pollination.

    ().

  Else

  % conduct local pollination.

   If  

    Draw a random vector .

    Draw two random integers j and .

    .

   Else

   Generate  byPerforming OL strategy according to Algorithm  1.

   End if

  End if

   Compute the fitness value .

   Update if the current individual is superior to its previous one.

  End for

  Find the pollen with the best fitness in the population.

  Update   if the current best pollen beats the previous best pollen.

  Perform catfish effect mechanism according to Algorithm  2.

  Return to the next generation until stop criterion is reached.

 End while

 Output .

End