Stochastic packing integer programs with few queries

Takanori Maehara, Yutaro Yamaguchi

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


We consider a stochastic variant of the packing-type integer linear programming problem, which contains random variables in the objective vector. We are allowed to reveal each entry of the objective vector by conducting a query, and the task is to find a good solution by conducting a small number of queries. We propose a general framework of adaptive and non-adaptive algorithms for this problem, and provide a unified methodology for analyzing the performance of those algorithms. We also demonstrate our framework by applying it to a variety of stochastic combinatorial optimization problems such as matching, matroid, and stable set problems.

Original languageEnglish
Pages (from-to)141-174
Number of pages34
JournalMathematical Programming
Issue number1-2
Publication statusPublished - Jul 1 2020
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Mathematics(all)


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