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arXiv CS.AI
7/15/2026
The original title is about LP Mining with LP2Graph for railway rescheduling. Let me rewrite this as a punchy headline.

The original title is about LP Mining with LP2Graph for railway rescheduling. Let me rewrite this as a punchy headline.

Original: LP Mining with LP2Graph: A Use Case for Railway Rescheduling

Short summary

LP2Graph is a method that mines published LP and MILP formulations into a reproducible dataset and induced taxonomy by representing each formulation as a typed variable-equation graph. Sources are parsed, homologized, and clustered by structure, application domain, and solution approach, then validated by regenerating LaTeX and re-solving across CBC, HiGHS, and Gurobi. The resulting objective taxonomy serves as the foundation for automated railway-rescheduling model development.

  • •LP2Graph converts published LP/MILP formulations into typed variable-equation graphs for reproducible analysis
  • •Clustering produces an objective taxonomy of variables, constraints, and model types validated by re-solving across three solvers
  • •Foundation for the raiLPminer line of automated railway-rescheduling model development

Generated with AI, which can make mistakes.

#research-breakthrough#open-source
Read full article at arXiv CS.AI

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