Research Article
A Hybrid Nondominant-Based Genetic Algorithm (NSGA-II) for Multiobjective Optimization to Minimize Vibration Amplitude in the End Milling Process
Table 7
Pareto-optimum solutions (NSGA-II).
| Sl. no. | N | | | | γ | Spindle vibration: predicted by NSGA-II ASV(NSGA-II) | Worktable vibration: predicted by NSGA-II AWTV(NSGA-II) |
| 1 | 2326.98 | 0.11 | 0.89 | 0.89 | 12.06 | 0.02404 | 0.00167 | 2 | 2324.31 | 0.12 | 0.89 | 0.89 | 12.06 | 0.02388 | 0.00165 | 3 | 2300.28 | 0.12 | 0.70 | 0.79 | 12.23 | 0.01450 | 0.00264 | 4 | 2288.40 | 0.17 | 0.70 | 0.69 | 12.47 | 0.01339 | 0.00284 | 5 | 2308.64 | 0.12 | 0.81 | 0.78 | 12.35 | 0.01599 | 0.00226 | 6 | 2320.46 | 0.12 | 0.88 | 0.85 | 12.07 | 0.02120 | 0.00177 | 7 | 2295.81 | 0.12 | 0.70 | 0.70 | 12.39 | 0.01336 | 0.00281 | 8 | 2316.22 | 0.12 | 0.84 | 0.78 | 12.24 | 0.01696 | 0.00214 | 9 | 2321.88 | 0.12 | 0.88 | 0.86 | 13.07 | 0.02199 | 0.00191 | 10 | 2299.54 | 0.12 | 0.79 | 0.76 | 12.26 | 0.01510 | 0.00231 | 11 | 2306.80 | 0.12 | 0.82 | 0.79 | 12.20 | 0.01670 | 0.00212 | 12 | 2289.54 | 0.12 | 0.70 | 0.70 | 12.40 | 0.01337 | 0.00282 | 13 | 2313.43 | 0.12 | 0.81 | 0.85 | 12.46 | 0.01866 | 0.00207 | 14 | 2322.56 | 0.12 | 0.85 | 0.84 | 12.07 | 0.01926 | 0.00190 | 15 | 2325.76 | 0.12 | 0.89 | 0.80 | 12.04 | 0.02391 | 0.00166 | 16 | 2318.48 | 0.12 | 0.87 | 0.82 | 12.57 | 0.01950 | 0.00198 | 17 | 2320.19 | 0.12 | 0.85 | 0.86 | 12.08 | 0.02034 | 0.00187 | 18 | 2300.56 | 0.12 | 0.76 | 0.73 | 12.24 | 0.01421 | 0.00247 | 19 | 2305.43 | 0.11 | 0.83 | 0.81 | 12.62 | 0.01761 | 0.00210 | 20 | 2319.12 | 0.12 | 0.77 | 0.76 | 12.12 | 0.01467 | 0.00239 | 21 | 2307.26 | 0.12 | 0.74 | 0.71 | 12.19 | 0.01367 | 0.00263 |
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