Table 1: Comparison of different multi-objective algorithms.

Target Equation Different Multi-objective Algorithms Average Improvement Percentage (%)
This Study (I) MOPSO (M) NSGAII (N) I:M I:N
Parameters setting Target equation (1)Best: 9,856,867.82; Worst:9,136,273.22;
Mean:9,432,921.12
Target equation (2)Best: 76.86; Worst:65.23;
Mean:71.38
Target equation (3)Best: 3.68; Worst:4.96;
Mean:3.72
Generations:300
Target equation (1)Best: 9,267,256.26; Worst: 9,061,256.06;
Mean:9,128,001.13
Target equation (2)Best: 71.08; Worst:63.29;
Mean:70.68
Target equation (3)Best: 4.31; Worst:6.92;
Mean:5.78. 300 Generations:300
Target equation (1)Best: 9,431,256.12; Worst: 9,178,224.16;
Mean:9,223,019.13
Target equation (2)Best: 74.11; Worst:66.26;
Mean:71.18
Target equation (3)Best: 3.98; Worst:6.12;
Mean:4.28. 300 Generations:300
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Target equation (1) (NT$) 9,856,867.82 9,267,256.26 9,431,256.12 6.36 4.51
Target equation (2) (%) 76.86 71.08 74.11 8.13 3.71
Target equation (3) (day) 3.68 4.31 3.98 14.62 7.54