Gradient-Based Cuckoo Search for Global Optimization

Algorithm 1

Simplified algorithm of the cuckoo search algorithm.

begin

 Objective function 𝑓(𝑥)

 Generate initial population of 𝑛 host nests 𝑥_𝑖

 while (t < MaxGeneration)

   Get a cuckoo randomly by Lévy flights

   Evaluate its quality/fitness

   Choose a nest among n (say, j) randomly

   If (𝐹_𝑖>𝐹_𝑗)

     Replace j by the new solution

   end

   A fraction (1−𝑝_𝑎) of nests are abandoned at random and new ones are built via random walk

   Keep the best solutions

   Rank the solutions and find the current best

 end while

 Postprocess results

end