dc.contributor.author | Roth, Maximilian | |
dc.date.accessioned | 2022-05-10T14:22:18Z | |
dc.date.available | 2022-05-10T14:22:18Z | |
dc.date.issued | 2022-05 | |
dc.identifier.uri | https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3460 | |
dc.identifier.uri | https://doi.org/10.48328/tudatalib-872 | |
dc.description | Optimization 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.iso | en | de_DE |
dc.rights | Open Data Commons Attribution License (ODC-By) v1.0 | |
dc.rights.uri | https://opendatacommons.org/licenses/by/1.0/ | |
dc.subject | MILP | de_DE |
dc.subject | MIQCP | de_DE |
dc.subject | Debugging | de_DE |
dc.subject | Pyomo | de_DE |
dc.subject | Python | de_DE |
dc.subject.classification | 409-02 Softwaretechnik und Programmiersprachen | de_DE |
dc.subject.ddc | 004 | |
dc.title | Debugging Tool for MILP and MIQCP formulations: obtaining constraints responsible for infeasible or unbounded pyomo models using Gurobi solver. | de_DE |
dc.type | Software | de_DE |
tud.unit | TUDa | |