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Table 2

Parameters configuration of each method

Algorithm Name of parameter Value
EMO-GOA The size of population (N) 30
Maximum number of iterations (maxIter) 100
The maximum value of c (c max) 1
The minimum value of c (c min) 0.004
The slack variable ε 0.001
The strength of attraction u; 0.5
The attractive length scale τ; 1.5
NS-MOGOA Has the same parameters as EMO-GOA except that there are no slack variables ε
MOGOA Has the same parameters as EMO-GOA except that there are no slack variables ε
SPEA2 The size of population (N) 30
Maximum number of iterations (maxIter) 100
The probability of crossover (P c) 0.9
The probability of mutation (P m) 0.1
The crossover distribution index for SBX (σ) 20
The mutation distribution index for PM (H) 20
GA The size of population (N) 30
Maximum number of iterations (maxIter) 100
The mutation rate (R m) 0.2
The crossover rate (R c) 0.9
PSO The size of population (N) 30
Maximum number of iterations (maxIter) 100
Learning factor (c 1) 2
Learning factor (c 2) 2
Inertia weight (w) 1.4

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