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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, 12:30-14:00
Room: 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

Status: accepted


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