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Approximation Algorithms for Stochastic Optimization (Dagstuhl Seminar 25132)

Authors Lisa Hellerstein, Viswanath Nagarajan, Kevin Schewior and all authors of the abstracts in this report

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DagRep.15.3.159.pdf
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Subject Classification

ACM Subject Classification
  • Mathematics of computing → Approximation algorithms
  • Mathematics of computing → Probability and statistics
Keywords
  • adaptivity
  • approximation algorithms
  • combinatorial optimization
  • stochastic optimization

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Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 25132 "Approximation Algorithms for Stochastic Optimization". In this seminar, we gathered researchers from different areas interested in combinatorial optimization problems in which there is some stochasticity in the input. The focus was on approximation algorithms for computing adaptive or non-adaptive strategies to interact with this stochastic uncertainty as well as structural measures such as the adaptivity gap.

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Lisa Hellerstein, Viswanath Nagarajan, and Kevin Schewior. Approximation Algorithms for Stochastic Optimization (Dagstuhl Seminar 25132). In Dagstuhl Reports, Volume 15, Issue 3, pp. 159-176, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/DagRep.15.3.159

Author Details

Lisa Hellerstein
  • NYU - New York, US
Viswanath Nagarajan
  • University of Michigan - Ann Arbor, US
Kevin Schewior
  • Universität Köln, DE
and all authors of the abstracts in this report
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