Documents disponibles écrits par cet auteur

New continuous-time scheduling formulation for continuous plants under variable electricity cost / Pedro M. Castro in Industrial & engineering chemistry research, Vol. 48 N° 14 (Juillet 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 14 (Juillet 2009) . - pp. 6701–6714 Titre : New continuous-time scheduling formulation for continuous plants under variable electricity cost Type de document : texte imprimé Auteurs : Pedro M. Castro, Auteur ; Iiro Harjunkoski, Auteur ; Ignacio E. Grossmann, Auteur Année de publication : 2009 Article en page(s) : pp. 6701–6714 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Continuous  plants  Scheduling  Time-dependent  electricity  pricing  Discrete-time  formulation  Continuous-time  formulation Résumé : This work addresses the scheduling of continuous plants subject to energy constraints related to time-dependent electricity pricing and availability. Discrete- and continuous-time formulations are presented that can address these issues together with multiple intermediate due dates. Both formulations rely on the resource−task network process representation. Their computational performance is compared for the objective of total electricity minimization with the results favoring the discrete-time model due to the more natural way of handling such a wide variety of discrete events. In particular, it can successfully handle problems of industrial size. Nevertheless, the new continuous-time model is a major breakthrough since it is the first model of its type that is able to effectively incorporate time-variable utility profiles. When compared to a simple manual scheduling procedure, the proposed scheduling approaches can lead to potential electricity savings around 20% by switching production from periods of high to low electricity cost. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900073k [article] New continuous-time scheduling formulation for continuous plants under variable electricity cost [texte imprimé] / Pedro M. Castro, Auteur ; Iiro Harjunkoski, Auteur ; Ignacio E. Grossmann, Auteur . - 2009 . - pp. 6701–6714. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 14 (Juillet 2009) . - pp. 6701–6714 Mots-clés : Continuous  plants  Scheduling  Time-dependent  electricity  pricing  Discrete-time  formulation  Continuous-time  formulation Résumé : This work addresses the scheduling of continuous plants subject to energy constraints related to time-dependent electricity pricing and availability. Discrete- and continuous-time formulations are presented that can address these issues together with multiple intermediate due dates. Both formulations rely on the resource−task network process representation. Their computational performance is compared for the objective of total electricity minimization with the results favoring the discrete-time model due to the more natural way of handling such a wide variety of discrete events. In particular, it can successfully handle problems of industrial size. Nevertheless, the new continuous-time model is a major breakthrough since it is the first model of its type that is able to effectively incorporate time-variable utility profiles. When compared to a simple manual scheduling procedure, the proposed scheduling approaches can lead to potential electricity savings around 20% by switching production from periods of high to low electricity cost. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900073k

Optimal short-term scheduling of large-scale multistage batch plants / Pedro M. Castro in Industrial & engineering chemistry research, Vol. 48 N° 24 (Décembre 2009) 

Public ISBD [article]  in Industrial & 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

Optimal short-term scheduling of large-scale multistage batch plants / Pedro M. Castro in Industrial & engineering chemistry research, Vol. 48 N° 24 (Décembre 2009) 

Public ISBD [article]  in Industrial & 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 : Chemical engineering Langues : Anglais (eng) Mots-clés : Large-scale  multiproduct  plants  Optimal  scheduling  Decomposition  algorithm 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. 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. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 24 (Décembre 2009) . - pp. 11002–11016 Mots-clés : Large-scale  multiproduct  plants  Optimal  scheduling  Decomposition  algorithm 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. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900734x