optimize-decision-modellisted

# Optimize Decision Model Translate an operational decision into a falsifiable mathematical model whose recommended solution can be independently checked. Read [references/optimization-modeling-method.md](references/optimization-modeling-method.md) before selecting a formulation or solver. ## Workflow 1. Define the decision owner, controllable actions, entities, horizon, frequency, latency, downstream effects, baseline policy, and terminal decision artifact. Separate controllable choices from forecasts and facts. 2. Declare sets, indices, parameters, units, sources, timestamps, uncertainty, missingness, and lineage. Reject inputs whose meaning or unit cannot be reconciled. 3. Define decision variables and domains before writing the objective. Include state, recourse, slack, and activation variables only when their operational meaning is explicit. 4. State the objective in business or system units. For multiple objectives, declare priority, lexicographic order, Pareto treatment, or calibrated trade-off weights; never hide policy choices inside arbitrary coefficients. Example: "maximize weekly shipped items subject to at most 3 in-flight batches and one review owner per PR" states units and constraints; "be more productive" does not. 5. Encode hard constraints separately from soft preferences and penalties. Bind every constraint to its operational rule, source, tolerance, and reason for being hard or relaxable. 6. Choose deterministic, scenario