Minimax regret for sourcing decisions

Model complexity should earn its place through better decisions, not novelty. This article explores minimax regret for sourcing decisions and the baselines needed to establish its incremental value.

Practitioner lens

A model for minimax regret for sourcing decisions should state its objective and feasible set explicitly. Hidden penalty weights or relaxed constraints can make an impressive result operationally impossible.

First experiment

Document assumptions and version the data, code, parameters and scenario set for reproducibility.

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