Research Article

A Bat Algorithm with Mutation for UCAV Path Planning

Algorithm 4

Algorithm of BAM for UCAV path planning.
Begin
 Step 1: Initialization. Set the generation counter ; Initialize the population of NP bats
    randomly and each bat corresponding to a potential solution to the given
   problem; define pulse frequency ; set loudness , the initial velocities and
   pulse rate ; set weighting factor .
 Step 2: Generating rotation coordinate system. Transform the original coordinate
   system into new rotation coordinate whose horizontal axis is the connection
   line from starting point to target point according to (1);
   convert battlefield threat information to the rotation coordinate system and
   divide the axis into equal partitions. Each feasible solution, denoted
   by P , is an array indicated by the composition of
   coordinates which are the floating-point numbers
Step 3: Evaluate the threat cost J for each bat in P by (4)
Step 4: while The halting criteria is not satisfied or MaxGeneration do
      Sort the population of bats P from best to worst by order of threat cost
      for each bat;
      for    : NP (all bats) do
          Select uniform randomly
          
          
          
          if (rand ) then
            
          else
            
          end if
          Evaluate the fitness for the offsprings , ,
          Select the offspring with the best fitness among the offsprings
             , ,
          if (rand ) then
             ;
          end if
        end for  
     Evaluate the threat cost for each bat in by (4).
     Sort the population of bats from best to worst by order of threat cost
     for each bat;
      ;
Step 5: end while
Step 6: Inversely transform the coordinates in final optimal path into the original
   coordinate, and output
End.