Table 8.

Parameter setting of HIOAs

Algorithms	Parameters	Description	Value initialized
Corona virus Herd Immunity Optimization (CHIO)	$C_0$	Number of initial infected case	1
	Max_Itr	Maximum number of iterations	1000
	HIS	Population Size	50
	$B{R}_r$	Basic Reproduction Rate	0.01
	$Ma{x}_{\mathit{Age}}$	Maximum age of the infected cases	100
	HIP	Herd Immunity Population	[0 or 1]
	R	Random Number	[0,1]
	$A_j$	Age Vector	1
	$S_j$	Status Vector	1
Forensic-Based Investigation Optimization (FBIO)	N	Population Size	50
	rand	Random Number	[–1,1]
	rand1	Random Number	[0,1]
	rand2	Random Number	[0,1]
	Α	Effectiveness coefficient	[–1,1]
Political Optimizer (PO)	N	Number of parties, constituencies, and members in each party	5
	$T_{\mathit{max}}$	Total number of iterations	500
	r	Random Number	[0,1]
	ƛ	party switching rate	1
Battle Royale Optimization (BRO)	iter	Maximum number of iterations	500
	Population_size	Population Size	50
	Threshold	Threshold	3
	r	Random Number	[0,1]
Heap-Based Optimizer (HBO)	T	Maximum number of iterations	500
	r	Random Number	[0,1]
	p	Random Number	[0,1]
	N	Size of Population	50
	D	Number of Dimension (variables)	30
	C	Number of Cycles (c = T/25)	8
Human Urbanization Algorithm (HUA)	t	Number of Iterations	500
	R	Random Number	[0,1]
	Ri	Random Number	[–1,1]
	K	Controlling diversification and intensification of adventurers	2
	Ripmk	Balancing between diversification and intensification in searching the city’s boundaries	1
	N	Population Size	50
Particle Swarm Optimization (PSO)	C1	Acceleration coefficients	2
	C2	Acceleration coefficients	2
	n	Population Size	50