Reoptimization Under Uncertainty is a computational framework in traffic flow management that, when disrupted by stochastic events, enables the dynamic revision of traffic control strategies through adaptive optimization techniques that explicitly account for uncertain future states and evolving system conditions.
25
Publications
1.1K
Citations
66
Authors
45
Institutions
Publications per year
2017–2026
12
Parents
Publications
25
1–5 of 25
Authors
66
- NS
3
h-index
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2
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2
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2
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2
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1–5 of 66
Institutions
45
KTH Royal Institute of Technology
Stockholm, Sweden
3 h-index
4 publications
132 citations
Zuse Institute Berlin
Berlin, Germany
2 h-index
2 publications
46 citations
University of Bayreuth
Bayreuth, Germany
2 h-index
2 publications
46 citations
University of Salerno
Fisciano, Italy
2 h-index
2 publications
46 citations
Cornell University
Ithaca, United States
2 h-index
2 publications
228 citations
Centre National de la Recherche Scientifique
Paris, France
2 h-index
3 publications
55 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
2 publications
124 citations
University of Illinois Chicago
Chicago, United States
2 h-index
2 publications
42 citations
1–8 of 45
Venues
- Operations Research
5 publications · 487 citations
5
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- Transportation Science
2 publications · 77 citations
2
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- Discrete Applied Mathematics
2 publications · 46 citations
2
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- IEEE Transactions on Industrial Informatics
1 publications · 22 citations
1
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- RAIRO - Operations Research
1 publications · 16 citations
1
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