Design for flexibility: An adjustable robust optimization approach with decision‐dependent uncertainty

Read full text
Authors: Jnana Sai Jagana, Sreekanth Rajagopalan, Satyajith Amaran, Q. Zhang
Cited by: 2
References: 41

Abstract

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.

Fields of Study & Subjects

Advanced Multi-Objective Optimization Algorithms Process Optimization and Integration Risk and Portfolio Optimization

Publication details

Journal / source
AIChE Journal
Publisher
Wiley
Volume
72
Issue
4
Publication date
19 January 2026
Language
EN