The Pareto Cover Problem

Bento Natura, Meike Neuwohner, Stefan Weltge

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We introduce the problem of finding a set B of k points in [0, 1]n such that the expected cost of the cheapest point in B that dominates a random point from [0, 1]n is minimized. We study the case where the coordinates of the random points are independently distributed and the cost function is linear. This problem arises naturally in various application areas where customers' requests are satisfied based on predefined products, each corresponding to a subset of features. We show that the problem is NP-hard already for k = 2 when each coordinate is drawn from {0, 1}, and obtain an FPTAS for general fixed k under mild assumptions on the distributions.

Original languageEnglish
Title of host publication30th Annual European Symposium on Algorithms, ESA 2022
EditorsShiri Chechik, Gonzalo Navarro, Eva Rotenberg, Grzegorz Herman
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959772471
DOIs
StatePublished - 1 Sep 2022
Event30th Annual European Symposium on Algorithms, ESA 2022 - Berlin/Potsdam, Germany
Duration: 5 Sep 20229 Sep 2022

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume244
ISSN (Print)1868-8969

Conference

Conference30th Annual European Symposium on Algorithms, ESA 2022
Country/TerritoryGermany
CityBerlin/Potsdam
Period5/09/229/09/22

Keywords

  • Approximation Algorithm
  • Covering
  • Optimization
  • Pareto

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