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Sensitivity analysis: A review of recent advances

Published on Feb 1, 2016in European Journal of Operational Research3.81
· DOI :10.1016/j.ejor.2015.06.032
Emanuele Borgonovo23
Estimated H-index: 23
(Bocconi University),
Elmar Plischke9
Estimated H-index: 9
(TUC: Clausthal University of Technology)
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Abstract
The solution of several operations research problems requires the creation of a quantitative model. Sensitivity analysis is a crucial step in the model building and result communication process. Through sensitivity analysis we gain essential insights on model behavior, on its structure and on its response to changes in the model inputs. Several interrogations are possible and several sensitivity analysis methods have been developed, giving rise to a vast and growing literature. We present an overview of available methods, structuring them into local and global methods. For local methods, we discuss Tornado diagrams, one way sensitivity functions, differentiation-based methods and scenario decomposition through finite change sensitivity indices, providing a unified view of the associated sensitivity measures. We then analyze global sensitivity methods, first discussing screening methods such as sequential bifurcation and the Morris method. We then address variance-based, moment-independent and value of information-based sensitivity methods. We discuss their formalization in a common rationale and present recent results that permit the estimation of global sensitivity measures by post-processing the sample generated by a traditional Monte Carlo simulation. We then investigate in detail the methodological issues concerning the crucial step of correctly interpreting the results of a sensitivity analysis. A classical example is worked out to illustrate some of the approaches.
  • References (188)
  • Citations (166)
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References188
Newest
#1Qingqing Zhai (Beihang University)H-Index: 12
#2Jun Yang (Beihang University)H-Index: 12
Last.Yu Zhao (Beihang University)H-Index: 9
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#1Leigang Zhang (NPU: Northwestern Polytechnical University)H-Index: 4
#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 18
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#1Leopoldo Eduardo Cárdenas-Barrón (Tec: Monterrey Institute of Technology and Higher Education)H-Index: 35
#2Kun-Jen Chung (Shih Chien University)H-Index: 14
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#1Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 18
Last.Jingwen Song (NPU: Northwestern Polytechnical University)H-Index: 6
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#1Barry J. Anderson (Bocconi University)H-Index: 2
#2Emanuele Borgonovo (Bocconi University)H-Index: 23
Last.Roberto Roson (Bocconi University)H-Index: 22
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#1Tianfeng Hou (Katholieke Universiteit Leuven)
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#1Stef Janssen (TU Delft: Delft University of Technology)H-Index: 1
#2Alexei Sharpanskykh (TU Delft: Delft University of Technology)H-Index: 13
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#1Amalia Pizarro-Alonso (DTU: Technical University of Denmark)H-Index: 1
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