| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
|---|
| Outline of Final Research Achievements |
In this research, we developed and examined a methodology of optimization methods that drastically improves optimization process for black box optimization, which is indispensable for solving engineering, energy and environmental problems. Considering that the bottleneck of optimization process is often hyper-parameter tuning based on trial-and-error, we tried to remove the need of the hyper-parameter tuning, so that the users can use the search algorithm out-of-the-box. We experimentally and theoretically analyzed the influence on hyper-parameter of search algorithms, and succeeded to derive the optimum values of some parameters. We also developed an adaptation mechanism for other preliminary parameters and succeeded in removing the hyper-parameter adjustment. In addition, we adopted statistical techniques and heuristic techniques to improve the search efficiency of methodology itself. The results of this research are expected to lead to the diffusion of optimization technology.
|
