Table 4:
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Metaheuristic algorithm parameters for PMS testing.

AlgorithmParameters
PSOLearning coefficient 1(personal): 1.5, Learning coefficient 2(global): 2.0, Inertia weight: 1.0
BBOMutation rate: 0.1, Keep coefficient: 0.2, Alpha: 0.9
DADragonfly population size: 20
GASelection pressure rate: 5, Mutation rate: 0.8, Crossover rate: 0.4
GOAGrasshopper population size: 20, |$cMin$|⁠: 0.00004, |$cMax$|⁠: 1
MFOMoth-flames population size: 20
FAInitial attraction rate: 2.0, Light absorption rate: 1.0, Mutation rate damping: 0.98, Mutation rate: 0.2
ALOAntlion population size: 20
IALOTAntlion population size: 20, random walk value: Max_Iter/5
AVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6
QEMAVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6, theta_ub:2π, theta_lb:0, Personal Learning coefficient: 2.05, Global Learning coefficient: 2.05, Inertia weight: 0.8
AlgorithmParameters
PSOLearning coefficient 1(personal): 1.5, Learning coefficient 2(global): 2.0, Inertia weight: 1.0
BBOMutation rate: 0.1, Keep coefficient: 0.2, Alpha: 0.9
DADragonfly population size: 20
GASelection pressure rate: 5, Mutation rate: 0.8, Crossover rate: 0.4
GOAGrasshopper population size: 20, |$cMin$|⁠: 0.00004, |$cMax$|⁠: 1
MFOMoth-flames population size: 20
FAInitial attraction rate: 2.0, Light absorption rate: 1.0, Mutation rate damping: 0.98, Mutation rate: 0.2
ALOAntlion population size: 20
IALOTAntlion population size: 20, random walk value: Max_Iter/5
AVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6
QEMAVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6, theta_ub:2π, theta_lb:0, Personal Learning coefficient: 2.05, Global Learning coefficient: 2.05, Inertia weight: 0.8
Table 4:
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Metaheuristic algorithm parameters for PMS testing.

AlgorithmParameters
PSOLearning coefficient 1(personal): 1.5, Learning coefficient 2(global): 2.0, Inertia weight: 1.0
BBOMutation rate: 0.1, Keep coefficient: 0.2, Alpha: 0.9
DADragonfly population size: 20
GASelection pressure rate: 5, Mutation rate: 0.8, Crossover rate: 0.4
GOAGrasshopper population size: 20, |$cMin$|⁠: 0.00004, |$cMax$|⁠: 1
MFOMoth-flames population size: 20
FAInitial attraction rate: 2.0, Light absorption rate: 1.0, Mutation rate damping: 0.98, Mutation rate: 0.2
ALOAntlion population size: 20
IALOTAntlion population size: 20, random walk value: Max_Iter/5
AVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6
QEMAVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6, theta_ub:2π, theta_lb:0, Personal Learning coefficient: 2.05, Global Learning coefficient: 2.05, Inertia weight: 0.8
AlgorithmParameters
PSOLearning coefficient 1(personal): 1.5, Learning coefficient 2(global): 2.0, Inertia weight: 1.0
BBOMutation rate: 0.1, Keep coefficient: 0.2, Alpha: 0.9
DADragonfly population size: 20
GASelection pressure rate: 5, Mutation rate: 0.8, Crossover rate: 0.4
GOAGrasshopper population size: 20, |$cMin$|⁠: 0.00004, |$cMax$|⁠: 1
MFOMoth-flames population size: 20
FAInitial attraction rate: 2.0, Light absorption rate: 1.0, Mutation rate damping: 0.98, Mutation rate: 0.2
ALOAntlion population size: 20
IALOTAntlion population size: 20, random walk value: Max_Iter/5
AVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6
QEMAVOAAlpha: 0.8, Betha: 0.2, Gamma:2.5, P1: 0.6, P2: 0.4, P3: 0.6, theta_ub:2π, theta_lb:0, Personal Learning coefficient: 2.05, Global Learning coefficient: 2.05, Inertia weight: 0.8
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