Observations in applying Bayesian versus evolutionary approaches and their hybrids in parallel time-constrained optimization
Abstract Parallel Surrogate-Based Optimization (PSBO) is an efficient approach to deal with
black-box time-consuming objective functions. According to the available computational …
black-box time-consuming objective functions. According to the available computational …
An Adaptive Parallel EI Infilling Strategy Extended by Non-Parametric PMC Sampling Scheme for Efficient Global Optimization
Y Hu, Y Guo, Z Liu, Y Li, Z Hu, D Shi, M Bu, S Du - IEEE Access, 2023 - ieeexplore.ieee.org
This paper presents a novel adaptive parallel Expected Improvement (EI) infilling strategy for
Efficient Global Optimization (EGO) by introducing a two-staged Non-parametric Population …
Efficient Global Optimization (EGO) by introducing a two-staged Non-parametric Population …
Batch Acquisition for Parallel Bayesian Optimization—Application to Hydro-Energy Storage Systems Scheduling
Bayesian Optimization (BO) with Gaussian process regression is a popular framework for
the optimization of time-consuming cost functions. However, the joint exploitation of BO and …
the optimization of time-consuming cost functions. However, the joint exploitation of BO and …
Contributions to the Analysis and Design of Parallel Batched Bayesian Optimization Algorithms
M Gobert - 2024 - hal.science
The optimization of computationally expensive black-box problems is a challenge faced in
many application fields. Those problems are characterized by the lack of information about …
many application fields. Those problems are characterized by the lack of information about …
Parallel Bayesian Optimization for Optimal Scheduling of Underground Pumped Hydro-Energy Storage Systems
Underground Pumped Hydro-Energy Storage stations are sustainable options to enhance
storage capacity and thus the flexibility of energy systems. Efficient management of such …
storage capacity and thus the flexibility of energy systems. Efficient management of such …
Space Partitioning with multiple models for Parallel Bayesian Optimization
Bayesian Optimization (BO) is a global optimization framework that uses bayesian surrogate
models such as Gaussian Processes (GP) to address black-box problems [1],[2] with costly …
models such as Gaussian Processes (GP) to address black-box problems [1],[2] with costly …