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Détail de l'auteur
Auteur Zhu, Lingyu
Documents disponibles écrits par cet auteur
Affiner la rechercheObject-oriented disjunctive programming with a nested heuristic and gradient-based solver for chemical process synthesis / Tian, Daqing in Industrial & engineering chemistry research, Vol. 49 N° 4 (Fevrier 2010)
[article]
in Industrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1779–1791
Titre : Object-oriented disjunctive programming with a nested heuristic and gradient-based solver for chemical process synthesis Type de document : texte imprimé Auteurs : Tian, Daqing, Auteur ; Zhu, Lingyu, Auteur ; Xi Chen, Auteur Année de publication : 2010 Article en page(s) : pp 1779–1791 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Disjunctive programming Chemical process synthesis. Résumé : The generalized disjunctive programming (GDP) model has been proposed and applied in the past decade as an alternative to the mixed integer nonlinear programming (MINLP) model because it has the advantages of being straightforward when used in conditional modeling and being able to reduce the complexity in the sub-NLP. In this paper, we introduced an improved variant of the traditional GDP model, otherwise known as the object-oriented disjunctive programming (ODP) model. Such a method helps generate well-posed sub-NLP, thereby improving the solving process. A nested method combining the heuristic algorithm and gradient-based optimizer is also proposed to solve the GDP and ODP. It is a two-layer method, wherein a heuristic algorithm performs master iterations in the outer-loop when dealing with the Boolean variables, and a gradient-based NLP solver is applied in the inner-loop when dealing with the sub-NLP. Excellent performance has been demonstrated by applying the modeling and solving methods into the process synthesis of heat exchanger networks (HENs) and water networks (WNs). DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901010a [article] Object-oriented disjunctive programming with a nested heuristic and gradient-based solver for chemical process synthesis [texte imprimé] / Tian, Daqing, Auteur ; Zhu, Lingyu, Auteur ; Xi Chen, Auteur . - 2010 . - pp 1779–1791.
Chimie industrielle
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1779–1791
Mots-clés : Disjunctive programming Chemical process synthesis. Résumé : The generalized disjunctive programming (GDP) model has been proposed and applied in the past decade as an alternative to the mixed integer nonlinear programming (MINLP) model because it has the advantages of being straightforward when used in conditional modeling and being able to reduce the complexity in the sub-NLP. In this paper, we introduced an improved variant of the traditional GDP model, otherwise known as the object-oriented disjunctive programming (ODP) model. Such a method helps generate well-posed sub-NLP, thereby improving the solving process. A nested method combining the heuristic algorithm and gradient-based optimizer is also proposed to solve the GDP and ODP. It is a two-layer method, wherein a heuristic algorithm performs master iterations in the outer-loop when dealing with the Boolean variables, and a gradient-based NLP solver is applied in the inner-loop when dealing with the sub-NLP. Excellent performance has been demonstrated by applying the modeling and solving methods into the process synthesis of heat exchanger networks (HENs) and water networks (WNs). DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901010a