[article] 
inIndustrial & engineering chemistry research > Vol. 48 N° 24 (Décembre 2009) . - pp. 11002–11016

Titre :	Optimal short-term scheduling of large-scale multistage batch plants
Type de document :	texte imprimé
Auteurs :	Pedro M. Castro, Auteur ; Iiro Harjunkoski, Auteur ; Ignacio E. Grossmann, Auteur
Année de publication :	2010
Article en page(s) :	pp. 11002–11016
Note générale :	Industrial chemistry
Langues :	Anglais (eng)
Mots-clés :	Optimal--Short-Term--Scheduling--Large-Scale--Multistage--Batch Plants
Résumé :	This paper presents a new decomposition algorithm for the optimal scheduling of large-scale multiproduct plants containing a large number of orders. Rather than tackling highly complex, full-space problems that cannot be solved in reasonable time, the complete set of orders is scheduled sequentially by considering one, or a couple of them, at a time. As we proceed through the iterations, previously scheduled orders can be partly rescheduled to allow for some flexibility while keeping the combinatorial complexity at a manageable level. Once a complete schedule is obtained, the same concept is applied to improve the schedule locally. The user can choose to rely on either a unit-specific or a sequencing variable based continuous-time mixed-integer linear programming model. In addition, there are other parameters that affect how the decomposition is carried out, so the algorithm is highly versatile and adaptable to problems of varying sizes. The largest problem solved is a real-life, 50-order, 17-unit, 6-stage problem, for which a very good solution can be found in less than 1 min of computational time.
ISSN :	0888-5885
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie900734x

[article] Optimal short-term scheduling of large-scale multistage batch plants [texte imprimé] / Pedro M. Castro, Auteur ; Iiro Harjunkoski, Auteur ; Ignacio E. Grossmann, Auteur . - 2010 . - pp. 11002–11016.
Industrial chemistry
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 48 N° 24 (Décembre 2009) . - pp. 11002–11016

Mots-clés :	Optimal--Short-Term--Scheduling--Large-Scale--Multistage--Batch Plants
Résumé :	This paper presents a new decomposition algorithm for the optimal scheduling of large-scale multiproduct plants containing a large number of orders. Rather than tackling highly complex, full-space problems that cannot be solved in reasonable time, the complete set of orders is scheduled sequentially by considering one, or a couple of them, at a time. As we proceed through the iterations, previously scheduled orders can be partly rescheduled to allow for some flexibility while keeping the combinatorial complexity at a manageable level. Once a complete schedule is obtained, the same concept is applied to improve the schedule locally. The user can choose to rely on either a unit-specific or a sequencing variable based continuous-time mixed-integer linear programming model. In addition, there are other parameters that affect how the decomposition is carried out, so the algorithm is highly versatile and adaptable to problems of varying sizes. The largest problem solved is a real-life, 50-order, 17-unit, 6-stage problem, for which a very good solution can be found in less than 1 min of computational time.
ISSN :	0888-5885
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie900734x