6 papers
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…
MazeMate: An LLM-Powered Chatbot to Support Computational Thinking in Gamified Programming Learning
Chenyu Hou, Hua Yu, Gaoxia Zhu +3
Computational Thinking (CT) is a foundational problem-solving skill, and gamified programming environments are a widely adopted approach to cultivating it. While large language mod…
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,…
Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects
Zihan Hong, Yushi Wu, Zhiting Zhao +4
With the recent progress in generative artificial intelligence (Generative AI), particularly in the development of large language models, recommendation systems are evolving to bec…
Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities
Jian Cheng Wong, Abhishek Gupta, Chin Chun Ooi +3
Deep learning models trained on finite data lack a complete understanding of the physical world. On the other hand, physics-informed neural networks (PINNs) are infused with such k…
Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons
Jiao Liu, Zhu Sun, Shanshan Feng +2
In the evolutionary computing community, the remarkable language-handling capabilities and reasoning power of large language models (LLMs) have significantly enhanced the functiona…