Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

Algorithm 1

Cuckoo search algorithm via Lévy flights as originally proposed by Yang and Deb in [21, 22].

begin

   Objective function 𝑓(𝐱), 𝐱=(𝑥₁,…,𝑥_𝐷)^𝑇

   Generate initial population of 𝑛 host nests 𝐱_𝑖    (𝑖=1,2,…,𝑛)

   While   (𝑡<MaxGeneration) or (stop criterion)

    Get a cuckoo (say, 𝑖) randomly by Lévy flights

    Evaluate its fitness 𝐹_𝑖

    Choose a nest among 𝑛 (say, 𝑗) randomly

     if (𝐹_𝑖>𝐹_𝑗)

     Replace 𝑗 by the new solution

     end

    A fraction (𝑝_𝑎) of worse nests are abandoned and new ones are built via Lévy flights

    Keep the best solutions (or nests with quality solutions)

    Rank the solutions and find the current best

   end while

   Postprocess results and visualization

end