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Study on sequence problem optimization using variation-robust multi-objective optimization genetic algorithm
oleh: Takashi YAMAZAKI, Akito MARUO, Ayano HASOME, Jun TANIGUCHI, Hajime IGARASHI
| Format: | Article |
|---|---|
| Diterbitkan: | The Japan Society of Mechanical Engineers 2022-10-01 |
Deskripsi
As a solution for sequence optimization, and to obtain a solution that is strong robustness to variations, a multi-objective robust design optimization (MORDO) and robust genetic algorithm (GA) are applied to a multi-objective optimization problem. As a result, it is found that the MORDO is a good method for obtaining a solution with strong robustness to condition variations, even in sequence problem optimization. Moreover, it is confirmed that the robust GA is advantageous as in regards to the calculation time. As a method for making the best use of these advantages, a hybrid method of the MORDO and robust GA is proposed and verified, and an optimum solution with the same robustness as that from the MORDO is obtained without huge loss of calculation time.