StockForge Optimizer Config

Configuration manifest for the StockForge retail decision intelligence engine.

Forecast Model

Optimizers

Optimizer Description
deterministic_inventory_milp Point forecast (P50) → reorder/safety stock MILP
stochastic_quantile_milp Expected cost over quantile scenarios
robust_quantile_milp Worst-case cost minimization

Solvers

Pyomo + HiGHS, scipy.stats fallback

Simulation

SimPy discrete-event inventory validation

No Training Required

This repository contains optimizer configuration and benchmark metadata only. Forecasting uses the pretrained Chronos-2 foundation model.

License

MIT

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