Dragonfly Algorithm and Its Applications in Applied Science Survey

Visual 4

Pseudocode for MHDA [26].

	Initializing the set of parameters:
	Maximum iteration (Max-iter), maximum number of search agents (N max) number of search agents (N), number of dimensions (d), upper bound and lower bound of variables. Initialize the dragonflies’ populations (X). Initialize the step vectors (ΔX)
	while maximum iterations not done
	For each dragonfly calculate fitness value
	If Fitness Value < DA-pbest
	In this iteration move the current value to DA-pbest matrix
	End if
	if fitness value < DA-
	set current value as DA-
	End if
	End
	For each dragonfly
	Update the food source and enemy
	Update , s, a, c, f, and e
	Calculate S, A, C, F, and E using Equtaions (2)–(6)
	Update neighbouring radius
	If a dragonfly has at least one neighbouring dragonfly
	Update velocity vector using equation (8) Update
	position vector using equation (9)
	Else
	Update position vector using equation (10)
	End if
	Check and correct new positions based on boundaries of variables
	End
	------------------End of DA and Start of PSO------------------
	For each particle
	Initialize particle with DA-pbest matrix Set PSO-as DA-
	End
	while maximum iterations or minimum error criteria is not attained
	For each particle
	Calculate fitness value
	If fitness value < PSO-pbest in history
	set current value as the new PSO-pbest
	End if
	End
	Choose the particle with the best fitness value of all the
	particles as the PSO-
	For each particle
	Calculate particle velocity according to equation (12)
	Update particle position according to equation (13)
	End
	End while