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424. Variable-size mixed-variable black-box optimization for central air conditioning configuration
Invited abstract in session MC-28: Advancements of OR-analytics in statistics, machine learning and data science 3, stream Advancements of OR-analytics in statistics, machine learning and data science.
Monday, 12:30-14:00Room: 065 (building: 208)
Authors (first author is the speaker)
| 1. | Shun Tanaka
|
| Information Science and Technology, Osaka University | |
| 2. | Shiho WATANABE
|
| TIC, Daikin Industries, Ltd. | |
| 3. | Hiroshi Morita
|
| The University of Osaka |
Abstract
We consider the variable-size mixed-variable black-box optimization, which involves variable dimensions and optimizing a diverse and numerous sets of variable types through a black-box function. In this study, we extend the mixed-variable black-box optimization problem and use estimation methods to achieve more efficient optimal solution search. This approach can be applied to find the equipment configuration of a central air conditioning system that provides an optimal configuration that minimizes overall installation and operating costs.
Keywords
- Computer Science/Applications
- Combinatorial Optimization
- Continuous Optimization
Status: accepted
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