The BAREFOOT Optimization Framework
Source abstract
Abstract
This work presents a description of the Batch Reification/Fusion Optimization Framework (BAREFOOT). BAREFOOT is a Bayesian Optimization (BO) Framework that has been built specifically for the aim of material optimization and design. The Framework combines multi-fidelity model fusion with batch BO to enable accelerated materials design. The Framework is built in Python and is available as open-source code. The Framework offers the capability to do pure Batch BO, pure Multi-Fidelity (sequential BO), or combine both methods. Since BO relies on acquisition functions, we have implemented many of the most commonly used acquisition functions in the Framework. Finally, the Framework is capable of both single- and multi-objective optimization approaches. This work presents an overview of the Framework and the calculation methods available and demonstrates the Framework’s performance based on generic optimization test functions.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Multi-Objective Optimization Algorithms · Optimal Experimental Design Methods · Probabilistic and Robust Engineering Design
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (58)
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