Global optimization of large-scale MIQCQPs via cluster decomposition: Application to short-term planning of an integrated refinery-petrochemical complex
Integrated refinery-petrochemical facilities are complex systems that require advanced decision-support tools for optimal short-term planning of their operations. The problem can be formulated as a mixed-integer quadratically constrained quadratic program (MIQCQP), in which discrete decisions select...
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| Published in: | Computers & chemical engineering Vol. 140; p. 106883 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
02.09.2020
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| Subjects: | |
| ISSN: | 0098-1354, 1873-4375 |
| Online Access: | Get full text |
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| Summary: | Integrated refinery-petrochemical facilities are complex systems that require advanced decision-support tools for optimal short-term planning of their operations. The problem can be formulated as a mixed-integer quadratically constrained quadratic program (MIQCQP), in which discrete decisions select operating modes for the process units, while the entire process network is represented by input-output relationships based on bilinear expressions describing yields and stream properties, pooling equations, fuels blending indices and cost indicators. We develop a novel decomposition-based algorithm for deterministic global optimization that divides the network into small clusters according to their functionality. Inside each cluster, we derive a mixed-integer linear programming (MILP) relaxation based on piecewise McCormick envelopes, dynamically partitioning the variables that belong to the cluster and reducing their domains through optimality-based bound tightening. Results for an industrial case study in Colombia show profit improvements above 10% and significantly reduced optimality gaps compared with the state-of-the-art global optimization solvers BARON and ANTIGONE. |
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| ISSN: | 0098-1354 1873-4375 |
| DOI: | 10.1016/j.compchemeng.2020.106883 |