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