Chance-constrained service planning

Model complexity should earn its place through better decisions, not novelty. This article explores chance-constrained service planning and the baselines needed to establish its incremental value.

Practitioner lens

A responsible implementation of chance-constrained service planning includes a fallback policy, approval thresholds, model-version records and a way to explain infeasible or conflicting recommendations.

First experiment

Write down the objective, constraints, uncertainty set and decision horizon before selecting a solver or model.

This is an original educational brief. It is a starting point for discussion, not a claim that one technique fits every supply chain.