Robust Optimization Made Easy with ROME

被引:63
作者
Goh, Joel [1 ]
Sim, Melvyn [2 ]
机构
[1] Natl Univ Singapore, NUS Business Sch, Stanford Grad Sch Business, Singapore 119245, Singapore
[2] Natl Univ Singapore, NUS Risk Management Inst, Singapore 119245, Singapore
关键词
APPROXIMATION; UNCERTAINTY; OPTIMALITY; POLICIES; SYSTEM;
D O I
10.1287/opre.1110.0944
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:973 / 985
页数:13
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