Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/316971 
Year of Publication: 
2024
Citation: 
[Journal:] Operations Research Forum [ISSN:] 2662-2556 [Volume:] 5 [Issue:] 2 [Article No.:] 48 [Publisher:] Springer International Publishing [Place:] Cham [Year:] 2024
Publisher: 
Springer International Publishing, Cham
Abstract: 
Abstract Algorithm configuration techniques automatically search for parameters of solvers and algorithms that provide minimal runtime or maximal solution quality on specified instance sets. Mixed-integer programming (MIP) solvers pose a particular challenge for algorithm configurators due to the difficulty of finding optimal, or even feasible, solutions on the large-scale problems commonly found in practice. We introduce the OPTANO Algorithm Tuner (OAT) to find configurations for MIP solvers and other optimization algorithms. We present and evaluate several critical components of OAT for solving MIPs in particular and show that OAT can find configurations that significantly improve the solution time of MIPs on two different datasets.
Subjects: 
Algorithm configuration
Mixed-integer programming
Large-scale problem instances
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Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version
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