A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling |
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Authors: | Sylvain MouretIgnacio E Grossmann Pierre Pestiaux |
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Affiliation: | a Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA b Total Refining & Marketing, Research Division, 76700 Harfleur, France |
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Abstract: | The aim of this paper is to introduce a methodology to solve a large-scale mixed-integer nonlinear program (MINLP) integrating the two main optimization problems appearing in the oil refining industry: refinery planning and crude-oil operations scheduling. The proposed approach consists of using Lagrangian decomposition to efficiently integrate both problems. The main advantage of this technique is to solve each problem separately. A new hybrid dual problem is introduced to update the Lagrange multipliers. It uses the classical concepts of cutting planes, subgradient, and boxstep. The proposed approach is compared to a basic sequential approach and to standard MINLP solvers. The results obtained on a case study and a larger refinery problem show that the new Lagrangian decomposition algorithm is more robust than the other approaches and produces better solutions in reasonable times. |
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Keywords: | Refinery planning Crude-oil scheduling Mixed-integer nonlinear programming Lagrangian decomposition |
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