A Fusion Crossover Mutation Sparrow Search Algorithm

Algorithm 2

Pseudocode of the ISSA.

	Initialize the parameters of SSA, for instance, the initial values of the upper and lower bound lb and ub and the maximum number of iterations T;
	Initialize the sparrow population Xi (i = 1, 2, …, N) by Algorithm 1;
	Calculate the fitness value fi of the individual sparrow;
	Obtain the current optimal position, the worst position, and the corresponding optimal fitness value and worst fitness value;
	While (t < T)
	For i = 1 to N
	Update the positions of the explorers using equation (12)
	Update the positions of the followers using equation (13)
	Update the positions of the forewarners using equation (4)
	End for
	For i = 1 to N
	Update fi and calculate the average fitness value favg of the sparrow population;
	if fi < favg
	Carry out Cauchy mutation according to equation (15)
	else
	Perform tent chaotic perturbance according to equation (17)
	end if
	Update fi and sort the individuals by fi;
	Retain the best first half of the individuals to promoted by SSA and directly enter the next generation;
	Select parents and offspring from the individuals that have been promoted to crossover and mutation using equations (18) and (19);
	Update the current optimal position, the worst position, and the corresponding optimal fitness value and worst fitness value;
	End for
	t = t + 1;
	End while
	Return X