Ambiguity-aware Optimization
Ambiguity-Aware Optimization is a risk optimization framework that explicitly accounts for uncertainty in probability distributions or model parameters by incorporating preferences over ambiguous outcomes, distinguishing it from conventional stochastic optimization methods through its sensitivity to epistemic uncertainty and robustness under distributional ambiguity.
32
Publications
2K
Citations
81
Authors
47
Institutions
Publications per year
2017–2026
17
Variants
Ambiguity Aware Optimization
Parents
32
Ambiguity in portfolio selection
Georg Ch. Pflug, David Wozabal · Quantitative Finance · 2007 · 268 citations
Ambiguous Risk Measures and Optimal Robust Portfolios
Giuseppe C. Calafiore · SIAM Journal on Optimization · 2007 · 173 citations
Business, Finance, Risk Management +17
A Soft Robust Model for Optimization Under Ambiguity
Aharon Ben‐Tal, Dimitris Bertsimas, David B. Brown · Operations Research · 2010 · 155 citations · Full text
Business, Decision Sciences, Finance +17
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47

UNSW Sydney
Sydney, Australia
2 h-index
4 publications
180 citations
University of Vienna
Vienna, Austria
2 h-index
3 publications
652 citations
Northwestern University
Evanston, United States
2 h-index
2 publications
59 citations
University of Michigan
Ann Arbor, United States
2 h-index
2 publications
194 citations
Copenhagen Business School
Copenhagen, Denmark
2 h-index
3 publications
162 citations
University of Münster
Münster, Germany
2 h-index
2 publications
135 citations
Shandong University
Jinan, China
2 h-index
2 publications
36 citations

University of International Business and Economics
Beijing, China
1 h-index
2 publications
34 citations
1–8 of 47
3 publications · 391 citations
3
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3 publications · 111 citations
3
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2 publications · 323 citations
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2 publications · 90 citations
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1 publications · 17 citations
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