5 papers
LLM-Based Exogenous World Modeling for Dynamic Scheduling
Ni Zhang, Haofeng Yuan, Jianan Zhou +2
Dynamic scheduling requires dispatching online arrivals while anticipating future jobs, as poor decisions can compound downstream costs under nonlinear tardiness objectives. We sho…
FormuEvo: LLM-Guided Evolution for Discovering Solver-Efficient Mixed-Integer Programming Formulations
Haofeng Yuan, Jianing Peng, Jieyi Bi +3
Mixed-integer programming (MIP) lies at the core of operations research and industrial optimization. While large language models (LLMs) have recently shown promise in automated MIP…
Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
Ni Zhang, Zhiguang Cao
Existing GFlowNet-based methods for vehicle routing problems (VRPs) typically employ Trajectory Balance (TB) to achieve global optimization but often neglect important aspects of l…
An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems
Ni Zhang, Zhiguang Cao, Jianan Zhou +2
Complex vehicle routing problems (VRPs) remain a fundamental challenge, demanding substantial expert effort for intent interpretation and algorithm design. While large language mod…
Adversarial Generative Flow Network for Solving Vehicle Routing Problems
Ni Zhang, Jingfeng Yang, Zhiguang Cao +1
Recent research into solving vehicle routing problems (VRPs) has gained significant traction, particularly through the application of deep (reinforcement) learning for end-to-end s…