GCWOAS2: Multiobjective Task Scheduling Strategy Based on Gaussian Cloud-Whale Optimization in Cloud Computing

Algorithm 3

Whale optimization algorithm based on the Gaussian cloud model.

	Input: the upper bound lb and lower bound ub of the solution space, the number of iterations iters, and number of search agent Num
	Output: The updated location of the whale .
(1)	For t = 1 to iters do
(2)	For i = 1 to Num do
(3)	Record current individual, select the best individual in the population and the worst individual .
(4)	if
(5)	Calculate the membership function of the Gaussian cloud model according to formula (29)
(6)	The membership function is used to update the new position of the whale in the swimming process as shown in formula (30).
(7)	else
(8)	According to the upper and lower bounds of the solution space, the number of iterations is dynamically adjusted , as in formula (31).
(9)	Calculate the membership function of the Gaussian cloud model according to formula (36).
(10)	The membership function is used to update the new position of the whale in the swimming process as shown in formula (37).
(11)	End for
(12)	End for