License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.OPODIS.2019.32
URN: urn:nbn:de:0030-drops-118187
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/11818/
Go to the corresponding LIPIcs Volume Portal

Emek, Yuval ; Harlev, Noga ; Izumi, Taisuke

Towards Distributed Two-Stage Stochastic Optimization

pdf-format:
LIPIcs-OPODIS-2019-32.pdf (0.5 MB)

Abstract

The weighted vertex cover problem is concerned with selecting a subset of the vertices that covers a target set of edges with the objective of minimizing the total cost of the selected vertices. We consider a variant of this classic combinatorial optimization problem where the target edge set is not fully known; rather, it is characterized by a probability distribution. Adhering to the model of two-stage stochastic optimization, the execution is divided into two stages so that in the first stage, the decision maker selects some of the vertices based on the probabilistic forecast of the target edge set. Then, in the second stage, the edges in the target set are revealed and in order to cover them, the decision maker can augment the vertex subset selected in the first stage with additional vertices. However, in the second stage, the vertex cost increases by some inflation factor, so the second stage selection becomes more expensive.
The current paper studies the two-stage stochastic vertex cover problem in the realm of distributed graph algorithms, where the decision making process (in both stages) is distributed among the vertices of the graph. By combining the stochastic optimization toolbox with recent advances in distributed algorithms for weighted vertex cover, we develop an algorithm that runs in time O(log (Δ) / ε), sends O(m) messages in total, and guarantees to approximate the optimal solution within a (3 + ε)-ratio, where m is the number of edges in the graph, Δ is its maximum degree, and 0 < ε < 1 is a performance parameter.

BibTeX - Entry

@InProceedings{emek_et_al:LIPIcs:2020:11818,
  author =	{Yuval Emek and Noga Harlev and Taisuke Izumi},
  title =	{{Towards Distributed Two-Stage Stochastic Optimization}},
  booktitle =	{23rd International Conference on Principles of Distributed Systems (OPODIS 2019)},
  pages =	{32:1--32:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-133-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{153},
  editor =	{Pascal Felber and Roy Friedman and Seth Gilbert and Avery Miller},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/11818},
  URN =		{urn:nbn:de:0030-drops-118187},
  doi =		{10.4230/LIPIcs.OPODIS.2019.32},
  annote =	{Keywords: weighted vertex cover, distributed graph algorithms, two-stage stochastic optimization, primal-dual}
}

Keywords: weighted vertex cover, distributed graph algorithms, two-stage stochastic optimization, primal-dual
Collection: 23rd International Conference on Principles of Distributed Systems (OPODIS 2019)
Issue Date: 2020
Date of publication: 11.02.2020

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI