TY - GEN
T1 - Stochastic packing integer programs with few queries
AU - Maehara, Takanori
AU - Yamaguchi, Yutaro
N1 - Publisher Copyright:
© Copyright 2018 by SIAM.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
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U2 - 10.1137/1.9781611975031.21
DO - 10.1137/1.9781611975031.21
M3 - Conference contribution
AN - SCOPUS:85045539366
T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
SP - 293
EP - 310
BT - 29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
A2 - Czumaj, Artur
PB - Association for Computing Machinery
T2 - 29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
Y2 - 7 January 2018 through 10 January 2018
ER -