Research team on (Meta-)Black-Box Optimization, Deep Reinforcement Learning and Large Language Model

Publications

Benchmarking MetaBBO Approaches

YearPaper
2026Chen Wang, Zeyuan Ma, et al. “Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering” The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026)
2025Zeyuan Ma, et al. “MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization” Advances in Neural Information Processing Systems 38 (NeurIPS 2025)
2023Zeyuan Ma, et al. “MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning.” Advances in Neural Information Processing Systems 36 (NeurIPS 2023. Oral).

MetaBBO Surveys

YearPaper
2024Zeyuan Ma, et al. “Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization.” IEEE Transactions on Evolutionary Computation (2025).

Developing MetaBBO Approaches

YearPaper
2025Hongshu Guo, Zeyuan Ma, et al. “DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization” Advances in Neural Information Processing Systems 38 (NeurIPS 2025).
2025Zeyuan Ma et. al. “Meta-Black-Box-Optimization through Offline Q-function Learning” (ICML 2025).
2025Zeyuan Ma et. al. “Surrogate Learning in Meta-Black-Box Optimization: A Preliminary Study” The Genetic and Evolutionary Computation Conference (2025).
2025Zeyuan Ma et. al. “Accurate Peak Detection in Multimodal Optimization via Approximated Landscape Learning” The Genetic and Evolutionary Computation Conference (2025).
2025Hongshu Guo et. al. “Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learning” The Genetic and Evolutionary Computation Conference (2025).
2025Hongshu Guo*, Zeyuan Ma*, Jiacheng Chen, et. al. “ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning” (AAAI 2025, Oral).
2024Hongshu Guo, Wenjie Qiu, Zeyuan Ma et. al. “Advancing CMA-ES with Learning-Based Cooperative Coevolution for Scalable Optimization” arXiv:2504.17578.
2024Zeyuan Ma*, Jiacheng Chen*, Hongshu Guo, et. al. “Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization” ICLR (2025).
2024Zeyuan Ma*, Jiacheng Chen*, Hongshu Guo, et. al. “Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning” The Genetic and Evolutionary Computation Conference (2024).
2024Hongqiao Lian, Zeyuan Ma, Hongshu Guo, et. al. “RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning” The Genetic and Evolutionary Computation Conference (2024).
2024Hongshu Guo, Zeyuan Ma, Jiacheng Chen, et. al. “Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution” IEEE Transactions on Systems, Man, and Cybernetics: Systems (2024).
2024Jiacheng Chen*, Zeyuan Ma*, et. al. “Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning” The Twelfth International Conference on Learning Representations (ICLR 2024).

Exploring AGI & Optimization

YearPaper
2025Zeyuan Ma, et. al. “Evolutionary System 2 Reasoning: An Empirical Proof” Journal of Intelligent and Sustainable Systems (2025).
2024Zeyuan Ma, Hongshu Guo, Jiacheng Chen, et. al. “LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation”.

Data-Driven Evolutionary Algorithms

YearPaper
2025Yuan-Ting Zhong, et al. “TRACE: A Generalizable Drift Detector for Streaming Data-Driven Optimization.” The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026).
2025Yuan-Ting Zhong, Yue-Jiao Gong. “Data-Driven Evolutionary Computation Under Continuously Streaming Environments: A Drift-Aware Approach.” IEEE Transactions on Evolutionary Computation (2025).
2024Yuan-Ting Zhong, et al. “Sddobench: A benchmark for streaming data-driven optimization with concept drift.” Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2024).
2024Yue-Jiao Gong, Yuan-Ting Zhong, Hao-Gan Huang. “Offline data-driven optimization at scale: A cooperative coevolutionary approach.” IEEE Transactions on Evolutionary Computation (2024).

Other Topics in Optimization

YearPaper
2025Wenjie Qiu et. al. “A Novel Two-Phase Cooperative Co-evolution Framework for Large-Scale Global Optimization with Complex Overlapping” The Genetic and Evolutionary Computation Conference (2025).
2023SC Lei, Hongshu Guo, et. al. “A High-Performance Tensorial Evolutionary Computation for Solving Spatial Optimization Problems” International Conference on Neural Information Processing (ICONIP 2023).
2021Zeyuan Ma, et. al. “An efficient computational approach for automatic itinerary planning on web servers” Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2021).