TY - JOUR
T1 - Stochastic packing integer programs with few queries
AU - Maehara, Takanori
AU - Yamaguchi, Yutaro
N1 - Funding Information:
The authors thank anonymous reviewers for their careful reading and a number of valuable comments. This work was supported by JSPS KAKENHI Grant Numbers 16H06931 and 16K16011.
PY - 2020/7/1
Y1 - 2020/7/1
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 - 10.1007/s10107-019-01388-x
DO - 10.1007/s10107-019-01388-x
M3 - Article
AN - SCOPUS:85063035422
SN - 0025-5610
VL - 182
SP - 141
EP - 174
JO - Mathematical Programming
JF - Mathematical Programming
IS - 1-2
ER -