Design for flexibility: An adjustable robust optimization approach with decision‐dependent uncertainty
Jnana Sai Jagana, Sreekanth Rajagopalan, Satyajith Amaran, Q. Zhang · AIChE Journal · 2026
ABSTRACT Flexibility is a crucial characteristic of industrial systems that face increasing volatilities and is therefore essential to ensure feasible operation under uncertainty. Flexibility is often closely tied to the design of a system, and careful consideration must be taken to understand the trade‐off between design cost and operational flexibility. In this work, we introduce a design optimization approach that we call design for flexibility , which incorporates a rigorous measure of flexibility directly into the objective function. We employ adjustable robust optimization to model uncertainty and allow for recourse in operational decisions. Compared to traditional flexibility analysis, the proposed approach can accommodate complex uncertainty sets beyond hyperrectangles as well as multiple flexibility indicators, allowing for a more comprehensive representation of uncertainty. We apply the proposed approach to three case studies, where the results demonstrate its versatility and effectiveness in rigorously evaluating the trade‐offs between cost and flexibility when designing industrial systems.