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dc.contributor.authorRoth, Maximilian
dc.date.accessioned2022-05-10T14:22:18Z
dc.date.available2022-05-10T14:22:18Z
dc.date.issued2022-05
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3460
dc.identifier.urihttps://doi.org/10.48328/tudatalib-872
dc.descriptionOptimization problems, in this case written in Pyomo, with modeling errors can lead to infeasibility of the model. From the perspective of the modeler, it is therefore essential to know which constraints lead to the infeasibility of the problem or which constraints are contradictory and which constraints have to be adjusted to make the model feasible. In this case, the IIS (Irreducible Inconsistent Subsystem) function of Gurobi is used as a basis, the interface to Pyomo is implemented and a structured output file is created.de_DE
dc.language.isoende_DE
dc.rightsOpen Data Commons Attribution License (ODC-By) v1.0
dc.rights.urihttps://opendatacommons.org/licenses/by/1.0/
dc.subjectMILPde_DE
dc.subjectMIQCPde_DE
dc.subjectDebuggingde_DE
dc.subjectPyomode_DE
dc.subjectPythonde_DE
dc.subject.classification409-02 Softwaretechnik und Programmiersprachende_DE
dc.subject.ddc004
dc.titleDebugging Tool for MILP and MIQCP formulations: obtaining constraints responsible for infeasible or unbounded pyomo models using Gurobi solver.de_DE
dc.typeSoftwarede_DE
tud.unitTUDa


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Open Data Commons Attribution License (ODC-By) v1.0
Except where otherwise noted, this item's license is described as Open Data Commons Attribution License (ODC-By) v1.0