Research Article
A DE-LS Metaheuristic Algorithm for Hybrid Flow-Shop Scheduling Problem considering Multiple Requirements of Customers
Table 4
Computational results about RPD and SD.
| Instances | Types | DE-LS | Without LS | Best/1 | Current-to-best/1 | Rand/1 | RPD | SD | RPD | SD | RPD | SD | RPD | SD | RPD | SD |
| 1 | J20-M3 | 0.00 | 0.00 | 0.54 | 0.77 | 0.72 | 1.17 | 0.45 | 1.04 | 0.10 | 0.21 | 2 | J20-M4 | 0.00 | 0.00 | 1.09 | 1.13 | 1.97 | 1.98 | 0.63 | 0.66 | 0.37 | 0.44 | 3 | J30-M3 | 0.12 | 0.25 | 2.11 | 3.27 | 2.56 | 4.22 | 1.52 | 2.41 | 1.24 | 2.31 | 4 | J30-M4 | 0.03 | 0.10 | 0.84 | 1.24 | 2.44 | 3.12 | 0.99 | 1.41 | 0.31 | 0.57 | 5 | J40-M3 | 0.16 | 0.49 | 1.13 | 2.50 | 3.10 | 6.71 | 1.79 | 3.95 | 1.22 | 2.63 | 6 | J40-M4 | 0.17 | 0.46 | 1.74 | 3.07 | 2.48 | 4.40 | 0.75 | 1.50 | 0.60 | 1.23 | 7 | J50-M3 | 0.26 | 0.73 | 0.82 | 2.38 | 1.56 | 4.04 | 0.88 | 2.27 | 0.49 | 1.32 | 8 | J50-M4 | 0.43 | 1.13 | 1.59 | 3.53 | 3.41 | 7.38 | 1.05 | 2.52 | 0.92 | 2.26 | 9 | J60-M3 | 0.35 | 1.10 | 1.34 | 4.11 | 2.40 | 7.11 | 0.93 | 3.03 | 1.25 | 3.94 | 10 | J60-M4 | 0.46 | 1.52 | 1.29 | 3.71 | 4.12 | 10.96 | 2.82 | 8.86 | 2.22 | 5.88 | 11 | J70-M3 | 0.97 | 3.74 | 2.56 | 8.58 | 4.11 | 13.58 | 2.26 | 7.55 | 3.49 | 11.32 | 12 | J70-M4 | 0.31 | 1.46 | 2.12 | 7.37 | 4.40 | 15.05 | 2.95 | 10.21 | 2.67 | 9.24 | 13 | J80-M3 | 0.75 | 3.42 | 2.99 | 13.08 | 4.77 | 20.11 | 2.78 | 12.00 | 4.23 | 17.87 | 14 | J80-M4 | 0.99 | 4.61 | 2.38 | 8.76 | 3.27 | 12.39 | 2.79 | 10.89 | 3.78 | 14.46 | 15 | J90-M3 | 0.31 | 1.43 | 0.67 | 3.15 | 1.30 | 5.99 | 0.65 | 3.41 | 1.93 | 8.10 | 16 | J90-M4 | 0.64 | 3.10 | 2.43 | 9.43 | 4.26 | 15.82 | 3.13 | 11.79 | 5.60 | 20.73 | 17 | J100-M3 | 0.55 | 2.61 | 1.11 | 5.04 | 2.14 | 9.41 | 1.37 | 7.00 | 3.20 | 14.33 | 18 | J100-M4 | 0.74 | 4.20 | 2.27 | 10.89 | 3.81 | 18.06 | 2.42 | 11.73 | 3.72 | 17.64 | Average | 0.40 | 1.69 | 1.61 | 5.11 | 2.93 | 8.97 | 1.68 | 5.68 | 2.07 | 7.47 |
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