A Bat Algorithm with Mutation for UCAV Path Planning

Algorithm 3

Bat algorithm with mutation.

Begin

 Step 1: Initialization. Set the generation counter 𝑡=1; Initialize the population of NP

   bats P randomly and each bat corresponding to a potential solution to the

   given problem; define loudness 𝐴; set frequency 𝑄 and the initial velocities 𝑣;

   set pulse rate 𝑟 and weighting factor 𝐹.

 Step 2: Evaluate the quality 𝑓 for each bat in 𝑃 determined by 𝑓(𝑥).

 Step 3: While the termination criteria is not satisfied or 𝑡 < MaxGeneration do

      Sort the population of bats P from best to worst by order of quality f for each bat;

      for  𝑖=1 : NP (all bats) do

        Select uniform randomly 𝑟₁≠𝑟₂≠𝑟₃≠𝑖

         𝑟₄=⌈𝑁𝑃∗rand⌉

         𝑣^𝑡_𝑖=𝑣_𝑖^𝑡−1+(𝑣^𝑡_𝑖−𝑥_∗)×𝑄

         𝑥^𝑡_𝑖=𝑥_𝑖^𝑡−1+𝑣^𝑡_𝑖

        if (rand > 𝑟) then

           𝑥^𝑡_𝑢=𝑥_∗+𝛼𝜀^𝑡

        else

           𝑥^𝑡_𝑢=𝑥^𝑡_𝑟1+𝐹(𝑥^𝑡_𝑟2−𝑥^𝑡_𝑟3)

        end if

        Evaluate the fitness for the offspring 𝑥^𝑡_𝑢, 𝑥^𝑡_𝑖, 𝑥^𝑡_𝑟4

        Select the offspring 𝑥^𝑡_𝑘 with the best fitness among the offsprings

          𝑥^𝑡_𝑢, 𝑥^𝑡_𝑖, 𝑥^𝑡_𝑟4

        if (rand < 𝐴) then

          𝑥^𝑡_𝑟4=𝑥^𝑡_𝑘;

        end if

      end for  𝑖

       𝑡=𝑡+1;

 Step 4: end while

 Step 5: Post-processing the results and visualization;

End.