AI RESEARCH
Agentic MIP Research: Accelerated Constraint Handler Generation
arXiv CS.AI
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ArXi:2605.09186v1 Announce Type: new Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a branch-and-cut solver requires substantial implementation, debugging, tuning, and large-scale benchmarking. We propose an agentic MIP research framework that shortens this feedback loop by embedding LLM agents into a solver-aware harness for generating, verifying, and evaluating plugins for the open-source solver.