Documents disponibles écrits par cet auteur

An efficient mixed-integer linear programming scheduling framework for addressing sequence-dependent setup issues in batch plants / Kopanos, Georgios M. in Industrial & engineering chemistry research, Vol. 48 N° 13 (Juillet 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 13 (Juillet 2009) . - pp. 6346–6357 Titre : An efficient mixed-integer linear programming scheduling framework for addressing sequence-dependent setup issues in batch plants Type de document : texte imprimé Auteurs : Kopanos, Georgios M., Auteur ; José Miguel Lainez, Auteur ; Puigjaner, Luis, Auteur Année de publication : 2009 Article en page(s) : pp. 6346–6357 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Mixed-integer  linear  programming  scheduling  framework  Sequence-dependent  setup  times Résumé : Setup times and/or costs appear in a plethora of industrial and service applications. Sequence-dependent setup times and costs entail significantly complex scheduling problems. In this paper, a new continuous time precedence-based mixed-integer linear programming scheduling framework is developed for dealing with sequence-dependent setup time and/or cost issues. This model is based on the unit-specific general precedence concept, which is introduced in this paper. Several case studies are carried out in order to highlight the efficiency and the special features of the proposed model. Comparisons were made with the existing precedence-based formulations. Medium-sized scheduling problems can be solved by the proposed framework with relatively low computational effort. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801127t [article] An efficient mixed-integer linear programming scheduling framework for addressing sequence-dependent setup issues in batch plants [texte imprimé] / Kopanos, Georgios M., Auteur ; José Miguel Lainez, Auteur ; Puigjaner, Luis, Auteur . - 2009 . - pp. 6346–6357. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 13 (Juillet 2009) . - pp. 6346–6357 Mots-clés : Mixed-integer  linear  programming  scheduling  framework  Sequence-dependent  setup  times Résumé : Setup times and/or costs appear in a plethora of industrial and service applications. Sequence-dependent setup times and costs entail significantly complex scheduling problems. In this paper, a new continuous time precedence-based mixed-integer linear programming scheduling framework is developed for dealing with sequence-dependent setup time and/or cost issues. This model is based on the unit-specific general precedence concept, which is introduced in this paper. Several case studies are carried out in order to highlight the efficiency and the special features of the proposed model. Comparisons were made with the existing precedence-based formulations. Medium-sized scheduling problems can be solved by the proposed framework with relatively low computational effort. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801127t

Pharmacokinetic based design of individualized dosage regimens using a bayesian approach / José Miguel Lainez in Industrial & engineering chemistry research, Vol. 50 N° 9 (Mai 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 5114–5130 Titre : Pharmacokinetic based design of individualized dosage regimens using a bayesian approach Type de document : texte imprimé Auteurs : José Miguel Lainez, Auteur ; Gary Blau, Auteur ; Linas Mockus, Auteur Année de publication : 2011 Article en page(s) : pp. 5114–5130 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Pharmacokinetic Résumé : Clinical trials and health care studies generate an enormous amount of data. This data is used by pharmaceutical companies during new drug development processes to characterize patient populations and determine a standardized dosage regimen for new patients, make commercial decisions, and gain approval from regulatory agencies. Nevertheless, the knowledge embedded in such data is rarely further exploited for customized patient care. In most cases, there is a significant difference between the pharmacokinetic profile of patients in a population, yet these differences are not reflected in the standardized dosage regimen. Here, a Bayesian methodology is proposed to individualize dosage regimens by combining the pharmacokinetic data collected from a patient population during clinical trials and additional data coming from a minimal number of serum samples from the new patient. In the Bayesian sense, the distribution of pharmacokinetic parameters from the population data is treated as prior information, and the posterior patient specific distribution of pharmacokinetic parameters is calculated. Then, such a posterior distribution is used to obtain dosage regimens that result in drug concentrations that are kept within the therapeutic window at a target confidence level for that patient. Moreover, a methodology is presented to suggest the sampling schedule for new patients so as to reduce the number of samples required to obtain well characterized individual pharmacometric parameters. Available pharmacokinetic data for Gabapentin, a therapeutic agent for epilepsy and neuropathic pain, is used to illustrate the concepts underlying the proposed strategy and the benefits of an individualized regimen over a standardized dosage regimen. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101610r [article] Pharmacokinetic based design of individualized dosage regimens using a bayesian approach [texte imprimé] / José Miguel Lainez, Auteur ; Gary Blau, Auteur ; Linas Mockus, Auteur . - 2011 . - pp. 5114–5130. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 5114–5130 Mots-clés : Pharmacokinetic Résumé : Clinical trials and health care studies generate an enormous amount of data. This data is used by pharmaceutical companies during new drug development processes to characterize patient populations and determine a standardized dosage regimen for new patients, make commercial decisions, and gain approval from regulatory agencies. Nevertheless, the knowledge embedded in such data is rarely further exploited for customized patient care. In most cases, there is a significant difference between the pharmacokinetic profile of patients in a population, yet these differences are not reflected in the standardized dosage regimen. Here, a Bayesian methodology is proposed to individualize dosage regimens by combining the pharmacokinetic data collected from a patient population during clinical trials and additional data coming from a minimal number of serum samples from the new patient. In the Bayesian sense, the distribution of pharmacokinetic parameters from the population data is treated as prior information, and the posterior patient specific distribution of pharmacokinetic parameters is calculated. Then, such a posterior distribution is used to obtain dosage regimens that result in drug concentrations that are kept within the therapeutic window at a target confidence level for that patient. Moreover, a methodology is presented to suggest the sampling schedule for new patients so as to reduce the number of samples required to obtain well characterized individual pharmacometric parameters. Available pharmacokinetic data for Gabapentin, a therapeutic agent for epilepsy and neuropathic pain, is used to illustrate the concepts underlying the proposed strategy and the benefits of an individualized regimen over a standardized dosage regimen. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101610r

Tracking the dynamics of the supply chain for enhanced production sustainability / Puigjaner, Luis in Industrial & engineering chemistry research, Vol. 48 N° 21 (Novembre 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 21 (Novembre 2009) . - pp. 9556–9570 Titre : Tracking the dynamics of the supply chain for enhanced production sustainability Type de document : texte imprimé Auteurs : Puigjaner, Luis, Auteur ; José Miguel Lainez, Auteur ; Carlos Rodrigo Álvarez, Auteur Année de publication : 2010 Article en page(s) : pp. 9556–9570 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Chain  design−planning  model  Scheduling  formulation Résumé : One of the key components of enterprise-wide optimization (EWO) is decision-making coordination and integration at all decision levels. In this paper, a supply chain design−planning model, which translates a recipe representation to the supply chain environment, is coupled with a scheduling formulation so that decision levels integration is achieved. This approach enabled us to assess the impact of considering scheduling aspects of process operations in the design of a supply chain network. A comparison of the proposed scheme and the traditional hierarchical approach shows the significance of such integration. Moreover, the scheduling details enable the dynamics of the supply chain to be tracked. We show the degree to which a holistic decision-making model within a model predictive control framework is able to react to incidents occurring in the supply chain components, including disturbances arising from local monitoring, control, and diagnosis of incidents in real time. Finally, a decomposition technique is applied to reduce the computational burden associated with the monolithic model solution. Validation of the proposed approach and the resulting potential benefits are highlighted by a case study. Moreover, the results obtained from this particular case study are examined and discussed with respect to future work. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801973n [article] Tracking the dynamics of the supply chain for enhanced production sustainability [texte imprimé] / Puigjaner, Luis, Auteur ; José Miguel Lainez, Auteur ; Carlos Rodrigo Álvarez, Auteur . - 2010 . - pp. 9556–9570. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 21 (Novembre 2009) . - pp. 9556–9570 Mots-clés : Chain  design−planning  model  Scheduling  formulation Résumé : One of the key components of enterprise-wide optimization (EWO) is decision-making coordination and integration at all decision levels. In this paper, a supply chain design−planning model, which translates a recipe representation to the supply chain environment, is coupled with a scheduling formulation so that decision levels integration is achieved. This approach enabled us to assess the impact of considering scheduling aspects of process operations in the design of a supply chain network. A comparison of the proposed scheme and the traditional hierarchical approach shows the significance of such integration. Moreover, the scheduling details enable the dynamics of the supply chain to be tracked. We show the degree to which a holistic decision-making model within a model predictive control framework is able to react to incidents occurring in the supply chain components, including disturbances arising from local monitoring, control, and diagnosis of incidents in real time. Finally, a decomposition technique is applied to reduce the computational burden associated with the monolithic model solution. Validation of the proposed approach and the resulting potential benefits are highlighted by a case study. Moreover, the results obtained from this particular case study are examined and discussed with respect to future work. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801973n