Research Article
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 |
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