A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

Algorithm 4

The main procedure of DE/CS.

Begin

 Step 𝟏 :  Initialization. Set the generation counter 𝐺=1; initialize the population 𝑃 of NP

    host nests randomly and each egg in a nest corresponding to a potential solution to

    the given problem; set the mutation scaling factor 𝐹 and crossover constant CR.

 Step 𝟐 :  While the termination criteria is not satisfied or  𝐺 < MaxGeneration do

     Sort the population/nests from best to worst.

     Store the best nests to KeepNest.

     Get a cuckoo (say, 𝑖) and replace its solution by performing Algorithm 3.

     𝐾=rand(NP,𝐷)>𝑝_𝑎.

     𝑃₁=𝑃; 𝑃₂=𝑃.

     for  𝑖=1 to NP do

       Step=rand∗(𝑌_𝑖−𝑍_𝑖);

       𝑋_new=𝑋_𝑖+Step⊙𝐾(𝑖,∶);

     end for

     for  𝑖=1 to NP do

       if 𝐹(𝑋_new)<𝐹(𝑋_𝑖)  then

         𝑋_new=𝑋_𝑖;𝐹(𝑋_new)=𝐹(𝑋_𝑖)

       end if

     end for

     Keep the best solutions/nests.

     Sort the population/nest from best to worst and find the current best.

     Replace the worst nests with the best nests KeepNest stored.

     Pass the current best to the next generation.

     𝐺=𝐺+1.

 Step   𝟑 : end while

 Step 𝟒 : Post-processing the results and visualization.

End.