Computing a Complex Network Hierarchical Structure for Financial Market Networks on the Basis of the Hybrid Heuristic Algorithm

Algorithm 1

GSA proposed to address CPM.

	Input:
	: number of generations;
	: size of population;
	:number of chromosomes;
	: crossover probability;
	: mutation probability;
	: maximum number of generations without improvement;
	T: annealing temperature;
	: annealing parameter.
	Output:
	Computing a complex network hierarchical structure for financial market networks on the basis of the hybrid heuristic algorithm
	Best structure outcome found for CPM.
(1)	Initialize population
(2)	Evaluate the error function of each chromosome in
(3)	Encode each chromosome in with binary code method.
(4)	While do
(5)	While ( ) do
(6)	For each in 1 to do
(7)	While (random deviate ) do
(8)	select chromosome at random from
(9)	select chromosome at random from
(10)	Crossover.
(11)	update
(12)	End while
(13)	While (random ) do 5
(14)	mutate
(15)	update ;
(16)	End while
(17)	Decode and evaluate error function of each chromosome in
(18)	If
(19)
(20)	End if
(21)
(22)
(23)	End while
(24)	End while