A Grasshopper Optimization-Based Approach for Task Assignment in Cloud Logistics

Algorithm 1

	Initialize the swarm Xi(i = 1, 2, …, n)
	Initialize cmax, cmin, and maximum numbers of iterations
	Calculate the fitness f1() and f2() of each search agent
	T = the best search agent
	While (l < Max number of iterations)
	Update c using (equation (18))
	for each search agent
	Normalize the distance between grasshoppers
	Update the position of the current search agent by equation (17)
	Bring the current agent back if it goes outside the boundaries
	end for
	Update T if there is a better solution
	l = l + 1
	end while
	Return T