Table 2 The offered RPCSO algorithm’s statistical examination over diverse traditional heuristic approaches.

Terms	OOA⁶	MAO⁷	SCO⁸	CSO³⁷	RPCSO
“Dataset 1”
“Best”	0.410454063	0.910353282	0.540082612	0.95338818	0.018069361
“Worst”	5.590398129	1.854675877	4.732999093	3.911659805	0.50564046
“Mean”	0.858517903	1.121954178	0.979063144	1.127535332	0.112643119
“Median”	0.512931198	0.910353282	0.540082612	0.95338818	0.018069361
“Std”	1.277195814	0.358400811	0.891855501	0.689565445	0.156968355
“Dataset 2”
“Best”	0.393224171	0.513451788	0.499691011	1.253183911	0.283597992
“Worst”	5.903362433	4.626162077	4.414968986	6.781762824	0.467442652
“Mean”	0.849215097	1.016578404	1.293196278	1.442212249	0.32920734
“Median”	0.393224171	0.559887285	0.816502108	1.253183911	0.328581887
“Std”	1.035067652	0.93836552	0.940730313	0.93986443	0.063687386
“Dataset3”
“Best”	0.437125662	0.934212309	0.572310456	0.962341234	0.02134224
“Worst”	5.621305692	1.873402142	4.765423472	3.934201234	0.52342276
“Mean”	0.872134569	1.145601235	0.987321452	1.142533023	0.13421178
“Median”	0.532456709	0.930124212	0.560023451	0.972290342	0.030311272
“Std”	1.294768142	0.373324521	0.912307832	0.703324567	0.173422378

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