Medium-Scale Expensive Optimization Framework with Weighted Committee- Based Surrogate-Assisted Differential Evolution: Application to Enhanced Geothermal Systems DOI

Xiaoqing Ren,

Hongliang Wang, Hanyu Hu

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

Abstract Real-world optimization challenges frequently involve computationally expensive evaluations, necessitating efficient strategies. To address the demands of medium-scale problems, this research introduces and explores a novel Weighted Committee-Based Surrogate-Assisted Differential Evolution Framework (WCBDEF). This framework innovatively combines principles from active learning ensemble learning, iteratively interrogating most ambiguous high-fidelity solutions to ensure judicious allocation evaluation resources. WCBDEF employs dual sampling criterion, with offline dedicated exploration online focused on exploitation. Benchmarking against state-of-the-art surrogate algorithms across six test functions reveals that demonstrates clear advantage in performance, confirming its efficacy tackling optimization. Moreover, application optimizing operational parameters for two Enhanced Geothermal Systems (EGS) models has resulted significant reduction Levelized Cost Electricity (LCOE), surpassing existing algorithmic solutions. The results demonstrate significantly outperforms methods, exhibiting superior performance over single surrogate-assisted evolutionary (SAEAs) real-world thereby showcasing exceptional potential solving problems.

Language: Английский

Weighted committee-based surrogate-assisted differential evolution framework for efficient medium-scale expensive optimization DOI

Xiaoqing Ren,

Hongliang Wang, Hanyu Hu

et al.

International Journal of Machine Learning and Cybernetics, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Language: Английский

Citations

0
Medium-Scale Expensive Optimization Framework with Weighted Committee- Based Surrogate-Assisted Differential Evolution: Application to Enhanced Geothermal Systems DOI

Xiaoqing Ren,

Hongliang Wang, Hanyu Hu

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

Abstract Real-world optimization challenges frequently involve computationally expensive evaluations, necessitating efficient strategies. To address the demands of medium-scale problems, this research introduces and explores a novel Weighted Committee-Based Surrogate-Assisted Differential Evolution Framework (WCBDEF). This framework innovatively combines principles from active learning ensemble learning, iteratively interrogating most ambiguous high-fidelity solutions to ensure judicious allocation evaluation resources. WCBDEF employs dual sampling criterion, with offline dedicated exploration online focused on exploitation. Benchmarking against state-of-the-art surrogate algorithms across six test functions reveals that demonstrates clear advantage in performance, confirming its efficacy tackling optimization. Moreover, application optimizing operational parameters for two Enhanced Geothermal Systems (EGS) models has resulted significant reduction Levelized Cost Electricity (LCOE), surpassing existing algorithmic solutions. The results demonstrate significantly outperforms methods, exhibiting superior performance over single surrogate-assisted evolutionary (SAEAs) real-world thereby showcasing exceptional potential solving problems.

Language: Английский

Citations

0