PittsburghV1, France, Analysis, bibRecord, 000662

A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

Identifieur interne : 000662 ( France/Analysis ); précédent : 000661; suivant : 000663

A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

Auteurs : Sylvain Mouret [États-Unis] ; Ignacio E. Grossmann [États-Unis] ; Pierre Pestiaux [France]

Source :

Computers & chemical engineering [ 0098-1354 ] ; 2011.

RBID : Pascal:12-0010769

Descripteurs français

Pascal (Inist)
- Lagrangien, Intégration, Ordonnancement, Gestion production, Raffinerie, Echelle grande, Programmation partiellement en nombres entiers, Programmation en nombres entiers, Programmation non linéaire, Industrie pétrolière, Multiplicateur Lagrange, Méthode plan sécant, Optimisation sousgradient, Norme, Planification, Effet non linéaire, Méthode décomposition, Résolution problème, Etude cas.
Wicri :
- topic : Industrie pétrolière, Norme.

English descriptors

KwdEn :
- Case study, Cutting plane method, Decomposition method, Integer programming, Integration, Lagrange multiplier, Lagrangian, Large scale, Mixed integer programming, Non linear effect, Non linear programming, Oil industry, Planning, Problem solving, Production management, Refinery, Scheduling, Standards, Subgradient optimization.

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.

Affiliations:

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Pascal:12-0010769

Le document en format XML

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<front><div type="abstract" xml:lang="en">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.</div>
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A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

Source :

Descripteurs français

English descriptors

Abstract

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Le document en format XML

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