Robust Optimization Made Easy with ROME

Authors:
Joel Goh;Melvyn Sim
Affiliations:
Stanford Graduate School of Business/ NUS Business School, National University of Singapore, Singapore 119245, Republic of Singapore;NUS Business School and NUS Risk Management Institute, National University of Singapore, Singapore 119245, Republic of Singapore
Venue:
Operations Research
Year:
2011

Citing 19
Cited 4

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Abstract

We introduce ROME, an algebraic modeling toolbox for a class of robust optimization problems. ROME serves as an intermediate layer between the modeler and optimization solver engines, allowing modelers to express robust optimization problems in a mathematically meaningful way. In this paper, we discuss how ROME can be used to model (1) a service-constrained robust inventory management problem, (2) a project-crashing problem, and (3) a robust portfolio optimization problem. Through these modeling examples, we highlight the key features of ROME that allow it to expedite the modeling and subsequent numerical analysis of robust optimization problems. ROME is freely distributed for academic use at http://www.robustopt.com.