Author

Yuan Tian

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#artificial intelligence Preprint Sep 2026

Surrogate-Assisted Genetic Programming with Phenotypic Characterisation in Dynamic Multi-Mode Project Scheduling

The experimental results show that binary encoding with Euclidean distance provides the most effective and robust surrogate guidance and highlight that effective surrogate-assisted GP depends not only on identifying promising offspring, but also on controlling redundancy and preserving useful diversity during evolution...

Yuan Tian, Yi Mei, Meng-Jie Zhang · 0 citations

Preprint Aug 2026

Accelerated Genetic Programming Hyper-Heuristics for Simulation-Based Scheduling via Agentic AI

This paper presents a systematic refactoring approach using Claude agentic AI on real-world project-scheduling workloads in a high-performance computing (HPC) environment, where the agent identifies bottlenecks, implements targeted optimizations, and evaluates their effects, while the researcher retains final control.

H. Li, A. Pletzer, Yuan Tian et al. · 0 citations

Preprint Jul 2026

Guiding Large Language Models with Genetic Programming-Evolved Heuristic Knowledge for Dynamic Multi-Mode Project Scheduling

This work transfers knowledge in the reverse direction, using knowledge extracted from high-quality GP rules to guide an online LLM decision maker, and injects it through Feature Selection, Feature Hint, Rule Reference, and Rule Follow.

Yuan Tian, Yi Mei, Mengjie Zhang · 1 citation