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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - An Experimental Comparison of Uncertainty Sets for Robust Shortest Path Problems
AU - Dokka Venkata Satyanaraya, Trivikram
AU - Goerigk, Marc
PY - 2017/9/1
Y1 - 2017/9/1
N2 - Through the development of efficient algorithms, data structures and preprocessing techniques,real-world shortest path problems in street networks are now very fast to solve. But in reality, theexact travel times along each arc in the network may not be known. This led to the developmentof robust shortest path problems, where all possible arc travel times are contained in a so-calleduncertainty set of possible outcomes.Research in robust shortest path problems typically assumes this set to be given, and providescomplexity results as well as algorithms depending on its shape. However, what can actually beobserved in real-world problems are only discrete raw data points. The shape of the uncertainty isalready a modelling assumption. In this paper we test several of the most widely used assumptionson the uncertainty set using real-world traffic measurements provided by the City of Chicago.We calculate the resulting different robust solutions, and evaluate which uncertainty approach isactually reasonable for our data. This anchors theoretical research in a real-world application andgives an indicator which robust models should be the future focus of algorithmic development.
AB - Through the development of efficient algorithms, data structures and preprocessing techniques,real-world shortest path problems in street networks are now very fast to solve. But in reality, theexact travel times along each arc in the network may not be known. This led to the developmentof robust shortest path problems, where all possible arc travel times are contained in a so-calleduncertainty set of possible outcomes.Research in robust shortest path problems typically assumes this set to be given, and providescomplexity results as well as algorithms depending on its shape. However, what can actually beobserved in real-world problems are only discrete raw data points. The shape of the uncertainty isalready a modelling assumption. In this paper we test several of the most widely used assumptionson the uncertainty set using real-world traffic measurements provided by the City of Chicago.We calculate the resulting different robust solutions, and evaluate which uncertainty approach isactually reasonable for our data. This anchors theoretical research in a real-world application andgives an indicator which robust models should be the future focus of algorithmic development.
KW - robust shortest paths
KW - uncertainty sets
KW - real-world data
KW - experimental study
M3 - Conference contribution/Paper
SN - 9781510849679
SN - 9783959770422
T3 - Open Access Series in Informatics
SP - 16:1-16:13
BT - Proceedings of the 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS2017)
A2 - D'Angelo, Gianlorenzo
A2 - Dollevoet, Twan
PB - Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
ER -