A stochastic probing problem with applications

Anupam Gupta, Viswanath Nagarajan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We study a general stochastic probing problem defined on a universe V, where each element e ∈ V is "active" independently with probability pe . Elements have weights {we : e ∈ V} and the goal is to maximize the weight of a chosen subset S of active elements. However, we are given only the pe values-to determine whether or not an element e is active, our algorithm must probe e. If element e is probed and happens to be active, then e must irrevocably be added to the chosen set S; if e is not active then it is not included in S. Moreover, the following conditions must hold in every random instantiation: - the set Q of probed elements satisfy an "outer" packing constraint, - the set S of chosen elements satisfy an "inner" packing constraint. The kinds of packing constraints we consider are intersections of matroids and knapsacks. Our results provide a simple and unified view of results in stochastic matching [1, 2] and Bayesian mechanism design [3], and can also handle more general constraints. As an application, we obtain the first polynomial-time Ω(1/k)-approximate "Sequential Posted Price Mechanism" under k-matroid intersection feasibility constraints, improving on prior work [3-5].

Original languageEnglish (US)
Title of host publicationInteger Programming and Combinatorial Optimization - 16th International Conference, IPCO 2013, Proceedings
Number of pages12
StatePublished - 2013
Event16th Conference on Integer Programming and Combinatorial Optimization, IPCO 2013 - Valparaiso, Chile
Duration: Mar 18 2013Mar 20 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7801 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th Conference on Integer Programming and Combinatorial Optimization, IPCO 2013

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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