Computational Intelligence and Neuroscience / 2019 / Article / Alg 2

Research Article

Gaussian Quantum Bat Algorithm with Direction of Mean Best Position for Numerical Function Optimization

Algorithm 2

Pseudocode of the QMBA algorithm.
Initialize the bat population and ;
Define pulse frequency , pulse rate and the loudness ;
while do
for to n do
  Generate new solutions by calculating the distance between the bat and current global best position, updating positions using   equations (7) and (8);
  if then
   if then
    Bats fly with quantum behavior and positions using equations (9)–(11);
   else
    The mean best position is used to guide other bats and position updated using equations (11) and (12);
   end if
  end if
  if then
   Accept the new solutions;
   Increase and reduce using equations (5) and (6);
  end if
  Rank the bats and find the current best ;
end for
;
end while

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