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Erscheinungsjahr: 
2024
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[Journal:] Operations Research Forum [ISSN:] 2662-2556 [Volume:] 5 [Issue:] 2 [Article No.:] 48 [Publisher:] Springer International Publishing [Place:] Cham [Year:] 2024
Verlag: 
Springer International Publishing, Cham
Zusammenfassung: 
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.
Schlagwörter: 
Algorithm configuration
Mixed-integer programming
Large-scale problem instances
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