3 papers
cs.NE2026
TransGP: Task-Conditioned Transformer-Guided Genetic Programming for Multitask Dynamic Flexible Job Shop Scheduling
Meng Xu, Jiao Liu, Hua Yu +1
Hyper-heuristics have become a popular approach for solving dynamic flexible job shop scheduling (DFJSS) problems. They use gradient-free optimization techniques like Genetic Progr…
cs.LG2025
EvoSpeak: Large Language Models for Interpretable Genetic Programming-Evolved Heuristics
Meng Xu, Jiao Liu, Yew Soon Ong
Genetic programming (GP) has demonstrated strong effectiveness in evolving tree-structured heuristics for complex optimization problems. Yet, in dynamic and large-scale scenarios,…
cs.NE2025
Quality Diversity Genetic Programming for Learning Scheduling Heuristics
Meng Xu, Frank Neumann, Aneta Neumann +1
Real-world optimization often demands diverse, high-quality solutions. Quality-Diversity (QD) optimization is a multifaceted approach in evolutionary algorithms that aims to genera…