Aircraft Control Parameter Estimation Using Self-Adaptive Teaching-Learning-Based Optimization with an Acceptance Probability

Algorithm 2 SaTLBO-AP.

Input: Maximum iteration number (maxiter), population size (nP).
Output: xbest, fbest.
Main algorithm
(1)	Initialise a set of population, pL_success, pT_success, pT_fail, pL_fail and .
(2)	For i = 1 to maxiter.
(2.1)	Identify the best solution, xbest, fbest and define xteacher = xbest.
(Teacher Phase)
For j = 1 to np
(2.2)	Generate pT based on pT_success, j, pT_fail,j.
(2.3)	Update the population using (10) based on the xteacher from (14).
(2.2.1)	Evaluate the objective function value.
(2.2.2)	Perform greedy selection.
(2.2.3)	Update pT_success, j, pT_fail,j using (17).
End
(Learner Phase)
For j = 1 to np
(2.4)	Generate pL based on pL_success, j, pL_fail,j.
(2.5)	Update the population using (18).
(2.5.1)	Evaluate the objective function value.
(2.5.2)	Perform greedy selection.
(2.5.3)	Update pL_success, j, pL_fail,j based on (17).
End
Update
(3)	End