The Secret to Reproducible and Portable Optimization: ORPilot’s Intermediate Representation (IR)

AI-generated optimization models often face challenges with reproducibility, but the ORPilot agent introduces an Intermediate Representation (IR) to solve this critical issue. The IR is a solver-agnostic JSON schema that captures the complete mathematical structure of an optimization problem, separating its abstract logic from any specific solver's code. This schema meticulously defines all components—including sets, parameters, variables, and constraints—and explicitly links them to their specific data sources. Consequently, the model becomes a portable and reusable asset that can be reliably re-run with updated data or a different solver, eliminating the need to regenerate code from an LLM.