Research1d ago
New Framework Audits Decision Engine Robustness
A new position paper proposes a post-solve audit layer for Mixed-Integer Linear Programming decision engines. This layer identifies how small perturbations in costs or demands invalidate nominally optimal plans. It provides solver-backed evidence of solution trust rather than replacing stochastic programming. Practitioners can now quantify the robustness gap in high-stakes industrial optimization pipelines.