logmip: a disjunctive 0–1 non-linear optimizer for process system models
Discrete-continuous non-linear optimization models are frequently used to formulate problems in process system engineering. Major modeling alternatives and solution algorithms include generalized disjunctive programming and mixed integer non-linear programming (MINLP). Both have advantages and drawb...
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| Veröffentlicht in: | Computers & chemical engineering Jg. 23; H. 4; S. 555 - 565 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
01.05.1999
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| ISSN: | 0098-1354, 1873-4375 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Discrete-continuous non-linear optimization models are frequently used to formulate problems in process system engineering. Major modeling alternatives and solution algorithms include generalized disjunctive programming and mixed integer non-linear programming (MINLP). Both have advantages and drawbacks depending on the problem they are dealing with. In this work, we describe the theory behind
logmip, a new computer code for disjunctive programming and MINLP. We discuss a hybrid modeling framework that combines both approaches, allowing binary variables and disjunctions for expressing discrete choices. An extension of the logic-based outer approximation (OA) algorithm has been implemented to solve the proposed hybrid model. Computational experience is reported on several examples, which are solved using disjunctive, MINLP and hybrid formulations. |
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| ISSN: | 0098-1354 1873-4375 |
| DOI: | 10.1016/S0098-1354(98)00293-2 |