26 papers
GeM-EA: A Generative and Meta-learning Enhanced Evolutionary Algorithm for Streaming Data-Driven Optimization
Yue Wu, Yuan-Ting Zhong, Ze-Yuan Ma +1
Streaming Data-Driven Optimization (SDDO) problems arise in many applications where data arrive continuously and the optimization environment evolves over time. Concept drift produ…
A Learning-Based Cooperative Coevolution Framework for Heterogeneous Large-Scale Global Optimization
Wenjie Qiu, Zixin Wang, Hongyu Fang +2
Cooperative Coevolution (CC) effectively addresses Large-Scale Global Optimization (LSGO) via decomposition but struggles with the emerging class of Heterogeneous LSGO (H-LSGO) pro…
COBRA++: Enhanced COBRA Optimizer with Augmented Surrogate Pool and Reinforced Surrogate Selection
Zipei Yu, Zhiyang Huang, Hongshu Guo +2
The optimization problems in realistic world present significant challenges onto optimization algorithms, such as the expensive evaluation issue and complex constraint conditions.…
Surrogate Ensemble in Expensive Multi-Objective Optimization via Deep Q-Learning
Yuxin Wu, Hongshu Guo, Ting Huang +2
Surrogate-assisted Evolutionary Algorithms~(SAEAs) have shown promising robustness in solving expensive optimization problems. A key aspect that impacts SAEAs' effectiveness is sur…
Reinforcement Learning-assisted Constraint Relaxation for Constrained Expensive Optimization
Qianhao Zhu, Sijie Ma, Zeyuan Ma +2
Constraint handling plays a key role in solving realistic complex optimization problems. Though intensively discussed in the last few decades, existing constraint handling techniqu…
Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
Chen Wang, Sijie Ma, Zeyuan Ma +1
Benchmark Design in Black-Box Optimization (BBO) is a fundamental yet open-ended topic. Early BBO benchmarks are predominantly human-crafted, introducing expert bias and constraini…