- Placement and Design
Simulation optimization
Reduce the repetition of trials in manufacturing.
- Discover good solutions with fewer trials, by combining Bayesian optimization with low-dimensionalization.
- Used to increase efficiency of design operations; e.g., for thermal power turbines and wind turbines.
Applications
- Optimize parameters for thermal power turbine design
- Optimize wind farm layout
- Investigate compositions in drug discovery and new functional materials
- Can be used to resolve problems where optimum parameters and combinations are determined by repeated trials
Benchmarks, strengths, and track record
- Low-dimension Bayesian optimization technologies reduce the number of trials by 50% compared to conventional methods
Inquiries
Please include the title “AI Technology Catalog: Simulation optimization” or the URL in the inquiry text.
Please note that because this technology is currently the subject of R&D activities, immediate responses to inquiries may not be possible.
References:
- Daiki Kiribuchi et.al.; “Modification of Bayesian optimization for efficient calibration of simulation models”; In 2020 Winter Simulation Conference (WSC),pp. 2821-2831, 2020.
