Abstract: Parallel Bayesian optimization is crucial for solving expensive black-box problems, yet batch acquisition strategies remain a challenge. To address this, we propose a novel parallel ...

Predicting the adhesive force between steel reinforcement and concrete is crucial as it influences stress distribution and the overall mechanical behavior of reinforced concrete. This study proposes a ...

ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Bayesian Optimization workflow (single- and multi-objective) built on botorch.org. It lets you declare design parameters and ...

High-intensity laser systems present unique measurement and optimization challenges due to their high complexity, low repetition rates, and shot-to-shot variations. We discuss recent developments ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free ...

ABSTRACT: The rapid prediction of aerodynamic performance is critical in the conceptual and preliminary design of hypersonic vehicles. This study focused on axisymmetric body configurations commonly ...

Massachusetts Institute of Technology, Department of Chemical Engineering, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States Drexel University, Department of Chemical and ...

Next to the primary optimization objectives, scientific optimization problems often contain a series of subordinate objectives, which can be expressed as preferences over either the outputs of an ...