5 papers
Large Language Model Assisted Automated Algorithm Generation and Evolution via Meta-black-box optimization
Xu Yang, Rui Wang, Kaiwen Li +2
Meta-black-box optimization has been significantly advanced through the use of large language models (LLMs), yet in fancy on constrained evolutionary optimization. In this work, Aw…
Deep Reinforcement Learning-Assisted Component Auto-Configuration of Differential Evolution Algorithm for Constrained Optimization: A Foundation Model
Xu Yang, Rui Wang, Kaiwen Li +2
Despite significant efforts to manually design high-performance evolutionary algorithms, their adaptability remains limited due to the dynamic and ever-evolving nature of real-worl…
Graph Attention Networks Unleashed: A Fast and Explainable Vulnerability Assessment Framework for Microgrids
Wei Liu, Tao Zhang, Chenhui Lin +2
Independent microgrids are crucial for supplying electricity by combining distributed energy resources and loads in scenarios like isolated islands and field combat. Fast and accur…
PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimization
Xu Yang, Rui Wang, Kaiwen Li +3
The landscape of optimization problems has become increasingly complex, necessitating the development of advanced optimization techniques. Meta-Black-Box Optimization (MetaBBO), wh…
Reinforcement learning Based Automated Design of Differential Evolution Algorithm for Black-box Optimization
Xu Yang, Rui Wang, Kaiwen Li +1
Differential evolution (DE) algorithm is recognized as one of the most effective evolutionary algorithms, demonstrating remarkable efficacy in black-box optimization due to its der…