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This paper describes several experiments to explore the options for solving a class of mixed integer nonlinear programming problems that stem from a real-world mine production planning project. The only type of nonlinear constraints in these problems are bilinear equalities involving continuous variables, which enforce the ratios between elements in mixed material streams. A branch-and-bound algorithm to handle the integer variables has been tried in another project. However, this branch-and-bound algorithm is not effective for handling the nonlinear constraints. Therefore state-of-the-art nonlinear solvers are utilized to solve the resulting nonlinear subproblems in this work. The experiments were carried out using the NEOS server for optimization. After finding that current nonlinear programming solvers seem to lack suitable preprocessing capabilities, we preprocess the instances beforehand and use an heuristic approach to solve the nonlinear subproblems. In the appendix, we explain how to add a polynomial constraint handler that uses IPOPT as embedded nonlinear programming solver for the constraint programming framework SCIP. This is one of the crucial steps for implementing our algorithm in SCIP. We briefly described our approach and give an idea of the work involved. |
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Experiments with nonlinear extensions to SCIP Andreas Bley; Thorsten Koch; Lingfeng Niu, Berlin-Dahlem Konrad-Zuse-Zentrum für Informationstechnik 2009, Online-Ressource (31 S., 229 KB) graph. Darst., Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, ZIB-Report / Konrad-Zuse-Zentrum für Informationstechnik Berlin 2008,28, Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden. - Auch als gedr. Ausg. vorhanden, This paper describes several experiments to explore the options for solving a class of mixed integer nonlinear programming problems that stem from a real-world mine production planning project. The only type of nonlinear constraints in these problems are bilinear equalities involving continuous variables, which enforce the ratios between elements in mixed material streams. A branch-and-bound algorithm to handle the integer variables has been tried in another project. However, this branch-and-bound algorithm is not effective for handling the nonlinear constraints. Therefore state-of-the-art nonlinear solvers are utilized to solve the resulting nonlinear subproblems in this work. The experiments were carried out using the NEOS server for optimization. After finding that current nonlinear programming solvers seem to lack suitable preprocessing capabilities, we preprocess the instances beforehand and use an heuristic approach to solve the nonlinear subproblems. In the appendix, we explain how to add a polynomial constraint handler that uses IPOPT as embedded nonlinear programming solver for the constraint programming framework SCIP. This is one of the crucial steps for implementing our algorithm in SCIP. We briefly described our approach and give an idea of the work involved., Systemvoraussetzungen: Acrobat reader., Archivierung/Langzeitarchivierung gewährleistet pdager DE-89, Forschungsbericht (DE-588)4155043-2 (DE-627)10467444X (DE-576)209815833 gnd-content, Bley, Andreas oth, Koch, Thorsten oth, Niu, Lingfeng oth, Konrad-Zuse-Zentrum für Informationstechnik Berlin ZIB-Report 2008,28 2008,28 (DE-627)478815719 (DE-576)433876018 (DE-600)2176854-7 2192-7782, http://webdoc.sub.gwdg.de/ebook/serien/ah/ZIB/ZR-08-28.pdf application/pdf Verlag kostenfrei Volltext, https://edocs.tib.eu/files/e01fn09/607882492.pdf application/pdf Verlag kostenfrei Volltext, https://edocs.tib.eu/files/e01fn09/607882492l.pdf application/pdf Verlag Leseprobe kostenfrei, DE-Zi4 epn:4127056002 del:202308180132, https://edocs.tib.eu/files/e01fn09/607882492.pdf LFER, LFER epn:3472085878 2019-05-07T00:00:00Z |
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Experiments with nonlinear extensions to SCIP, Konrad-Zuse-Zentrum für Informationstechnik Berlin, ZIB-Report, 2008,28, This paper describes several experiments to explore the options for solving a class of mixed integer nonlinear programming problems that stem from a real-world mine production planning project. The only type of nonlinear constraints in these problems are bilinear equalities involving continuous variables, which enforce the ratios between elements in mixed material streams. A branch-and-bound algorithm to handle the integer variables has been tried in another project. However, this branch-and-bound algorithm is not effective for handling the nonlinear constraints. Therefore state-of-the-art nonlinear solvers are utilized to solve the resulting nonlinear subproblems in this work. The experiments were carried out using the NEOS server for optimization. After finding that current nonlinear programming solvers seem to lack suitable preprocessing capabilities, we preprocess the instances beforehand and use an heuristic approach to solve the nonlinear subproblems. In the appendix, we explain how to add a polynomial constraint handler that uses IPOPT as embedded nonlinear programming solver for the constraint programming framework SCIP. This is one of the crucial steps for implementing our algorithm in SCIP. We briefly described our approach and give an idea of the work involved., Forschungsbericht |
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