Documents disponibles écrits par cet auteur

Integrated operational planning and medium-term scheduling for large-scale industrial batch plants / Peter M. Verderame in Industrial & engineering chemistry research, Vol. 47 n°14 (Juillet 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 n°14 (Juillet 2008) . - p. 4845–4860 Titre : Integrated operational planning and medium-term scheduling for large-scale industrial batch plants Type de document : texte imprimé Auteurs : Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur Année de publication : 2008 Article en page(s) : p. 4845–4860 Langues : Anglais (eng) Mots-clés : Batch  chemical  plants;  Planning;  Scheduling;  Integrative  framework Résumé : The operational planning and the medium-term scheduling of a multipurpose and multiproduct batch chemical plant are inter-related activities that involve the allocation of plant resources. Because of their disparate time scales, however, the effective integration of planning and scheduling has proven to be a formidable task. The lack of an integrative framework for planning and scheduling will invariably cause the planning model to provide unrealistic production targets to the scheduling level, leading to the misallocation of plant resources. In response to this issue, a novel framework for the integration of planning and scheduling for a multipurpose and multiproduct batch plant is presented. The framework entails integrating a novel planning with production disaggregation model with a medium-term scheduling model through a forward-rolling horizon approach. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8001414 [article] Integrated operational planning and medium-term scheduling for large-scale industrial batch plants [texte imprimé] / Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur . - 2008 . - p. 4845–4860. Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 n°14 (Juillet 2008) . - p. 4845–4860 Mots-clés : Batch  chemical  plants;  Planning;  Scheduling;  Integrative  framework Résumé : The operational planning and the medium-term scheduling of a multipurpose and multiproduct batch chemical plant are inter-related activities that involve the allocation of plant resources. Because of their disparate time scales, however, the effective integration of planning and scheduling has proven to be a formidable task. The lack of an integrative framework for planning and scheduling will invariably cause the planning model to provide unrealistic production targets to the scheduling level, leading to the misallocation of plant resources. In response to this issue, a novel framework for the integration of planning and scheduling for a multipurpose and multiproduct batch plant is presented. The framework entails integrating a novel planning with production disaggregation model with a medium-term scheduling model through a forward-rolling horizon approach. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8001414

Integration of operational planning and medium - term scheduling for large - scale industrial batch plants under demand and processing time uncertainty / Peter M. Verderame in Industrial & engineering chemistry research, Vol. 49 N° 10 (Mai 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 10 (Mai 2010) . - pp. 4948–4965 Titre : Integration of operational planning and medium - term scheduling for large - scale industrial batch plants under demand and processing time uncertainty Type de document : texte imprimé Auteurs : Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur Année de publication : 2010 Article en page(s) : pp. 4948–4965 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Operational  Planning Résumé : Operational planning, medium-term scheduling, and short-term scheduling are closely related activities. Despite prior advances, the effective integration of planning and scheduling under demand and processing time uncertainty remains a challenging problem, especially for large-scale industrial processes. To address this issue, a novel framework for the integration of planning and scheduling under demand due date and amount uncertainty, as well as batch processing time uncertainty is proposed. Both the robust operational planning with production disaggregation model and the operational conditional value-at-risk planning with production disaggregation model have been successfully interfaced with an industrially validated medium-term scheduling model by means of a rolling horizon framework used in conjunction with a novel feedback loop. Demand uncertainty is taken into account at the planning level, processing time uncertainty is addressed within the selected scheduling model, and a novel feedback loop allows for the two-way interaction between the planning and scheduling levels. An industrial case study has been conducted for a large-scale multipurpose and multiproduct batch plant capable of producing hundreds of products over a time horizon of 3 months in order to demonstrate the viability of the proposed approach. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901973e [article] Integration of operational planning and medium - term scheduling for large - scale industrial batch plants under demand and processing time uncertainty [texte imprimé] / Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur . - 2010 . - pp. 4948–4965. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 10 (Mai 2010) . - pp. 4948–4965 Mots-clés : Operational  Planning Résumé : Operational planning, medium-term scheduling, and short-term scheduling are closely related activities. Despite prior advances, the effective integration of planning and scheduling under demand and processing time uncertainty remains a challenging problem, especially for large-scale industrial processes. To address this issue, a novel framework for the integration of planning and scheduling under demand due date and amount uncertainty, as well as batch processing time uncertainty is proposed. Both the robust operational planning with production disaggregation model and the operational conditional value-at-risk planning with production disaggregation model have been successfully interfaced with an industrially validated medium-term scheduling model by means of a rolling horizon framework used in conjunction with a novel feedback loop. Demand uncertainty is taken into account at the planning level, processing time uncertainty is addressed within the selected scheduling model, and a novel feedback loop allows for the two-way interaction between the planning and scheduling levels. An industrial case study has been conducted for a large-scale multipurpose and multiproduct batch plant capable of producing hundreds of products over a time horizon of 3 months in order to demonstrate the viability of the proposed approach. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901973e

Multisite planning under demand and transportation time uncertainty / Peter M. Verderame 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. 4959-4982 Titre : Multisite planning under demand and transportation time uncertainty : robust optimization and conditional value-at-risk frameworks Type de document : texte imprimé Auteurs : Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur Année de publication : 2011 Article en page(s) : pp. 4959-4982 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Optimization  Uncertainty  Planning Résumé : The operational planning of a multisite production and distribution network entails determining the daily production and shipment profiles for the supply chain under consideration. The generated profiles should provide a tight upper bound on the true production capacity of the supply chain to ensure the maximization of customer satisfaction along with the minimization of resource misallocation. With an operational planning time horizon of 1―3 months, it is also imperative to take into account pertinent parameter uncertainty, so that the production and shipment profiles are not only a tight upper bound on the supply chain's production capacity but also immune to the different forms of system uncertainty, such as demand due date, demand amomt, and transportation time uncertainty. These types of uncertainty have been explicitly considered by means of the robust optimization framework and conditional value-at-risk theory. An industrial case study has been undertaken to demonstrate the viability of the proposed multisite operational planning under uncertainty approaches. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128627 [article] Multisite planning under demand and transportation time uncertainty : robust optimization and conditional value-at-risk frameworks [texte imprimé] / Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur . - 2011 . - pp. 4959-4982. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 4959-4982 Mots-clés : Optimization  Uncertainty  Planning Résumé : The operational planning of a multisite production and distribution network entails determining the daily production and shipment profiles for the supply chain under consideration. The generated profiles should provide a tight upper bound on the true production capacity of the supply chain to ensure the maximization of customer satisfaction along with the minimization of resource misallocation. With an operational planning time horizon of 1―3 months, it is also imperative to take into account pertinent parameter uncertainty, so that the production and shipment profiles are not only a tight upper bound on the supply chain's production capacity but also immune to the different forms of system uncertainty, such as demand due date, demand amomt, and transportation time uncertainty. These types of uncertainty have been explicitly considered by means of the robust optimization framework and conditional value-at-risk theory. An industrial case study has been undertaken to demonstrate the viability of the proposed multisite operational planning under uncertainty approaches. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128627

Operational planning of large - scale continuous processes / Jie Li in Industrial & engineering chemistry research, Vol. 51 N° 11 (Mars 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 11 (Mars 2012) . - pp. 4347–4362 Titre : Operational planning of large - scale continuous processes : Deterministic planning model and robust optimization for demand amount and due date uncertainty Type de document : texte imprimé Auteurs : Jie Li, Auteur ; Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur Année de publication : 2012 Article en page(s) : pp. 4347–4362 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Uncertainty  Optimization  Modeling  Continuous  process  Planning Résumé : The operational planning problem typically determines both the plant’s aggregate and daily production targets to meet product demands over a long time horizon varying from one to three months. The daily production profile generated from the operational planning level is used to schedule the day-to-day operations of the plant. In this paper, we first extend the production disaggregation model framework proposed by Verderame and Floudas, Ind. Eng. Chem. Res.2008, 47, 4845–4860 to develop a novel mixed-integer linear programming operational planning model based on discrete-time representation for a large-scale multiproduct continuous plant. We allow unused processing time to carry over from one day to the next and thus capture the continuous time nature of the plant. The production totals are disaggregated into a feasible distribution of daily production requirements, and daily production profiles are provided to meet the requirements of the medium-term scheduling model developed by Shaik and Floudas, Comput. Chem. Eng.2009, 33, 670–686. Then, we extend the work of Lin et al. Ind. Eng. Chem. Res.2004, 28, 1069–1085 and Janak et al. Ind. Eng. Chem. Res.2007, 31, 171–195 to address various forms of demand amount and due date uncertainty. The computational results show that the proposed deterministic and robust planning models successfully provide tight upper bounds on the plant’s true production capacity. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25655642 [article] Operational planning of large - scale continuous processes : Deterministic planning model and robust optimization for demand amount and due date uncertainty [texte imprimé] / Jie Li, Auteur ; Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur . - 2012 . - pp. 4347–4362. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 11 (Mars 2012) . - pp. 4347–4362 Mots-clés : Uncertainty  Optimization  Modeling  Continuous  process  Planning Résumé : The operational planning problem typically determines both the plant’s aggregate and daily production targets to meet product demands over a long time horizon varying from one to three months. The daily production profile generated from the operational planning level is used to schedule the day-to-day operations of the plant. In this paper, we first extend the production disaggregation model framework proposed by Verderame and Floudas, Ind. Eng. Chem. Res.2008, 47, 4845–4860 to develop a novel mixed-integer linear programming operational planning model based on discrete-time representation for a large-scale multiproduct continuous plant. We allow unused processing time to carry over from one day to the next and thus capture the continuous time nature of the plant. The production totals are disaggregated into a feasible distribution of daily production requirements, and daily production profiles are provided to meet the requirements of the medium-term scheduling model developed by Shaik and Floudas, Comput. Chem. Eng.2009, 33, 670–686. Then, we extend the work of Lin et al. Ind. Eng. Chem. Res.2004, 28, 1069–1085 and Janak et al. Ind. Eng. Chem. Res.2007, 31, 171–195 to address various forms of demand amount and due date uncertainty. The computational results show that the proposed deterministic and robust planning models successfully provide tight upper bounds on the plant’s true production capacity. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25655642

Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. robust optimization framework / Peter M. Verderame in Industrial & engineering chemistry research, Vol. 48 N° 15 (Août 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 15 (Août 2009) . - pp. 7214–7231 Titre : Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. robust optimization framework Type de document : texte imprimé Auteurs : Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur Année de publication : 2009 Article en page(s) : pp. 7214–7231 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Large-scale  industrial  batch  plant  Operational  planning  model Résumé : The operational planning of a large-scale industrial batch plant typically occurs over a time horizon of several months with the goal of providing daily production targets and raw material requirements for the plant in question. Due to the length of the time horizon, demand uncertainty should be taken into account in order to ensure that the operational planning model provides reliable production targets and/or raw material requirements. A robust novel operational planning model has been developed in order to address the objective of providing a reliable daily production profile which is immune to various forms of demand uncertainty. The ability of the proposed planning model to address the aforementioned objectives of an operational planning model has been validated through an industrial case study of a large-scale, multiproduct, and multipurpose batch plant having the capability of producing hundreds of different products over a time horizon of three months. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9001124 [article] Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. robust optimization framework [texte imprimé] / Peter M. Verderame, Auteur ; Christodoulos A. Floudas, Auteur . - 2009 . - pp. 7214–7231. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 15 (Août 2009) . - pp. 7214–7231 Mots-clés : Large-scale  industrial  batch  plant  Operational  planning  model Résumé : The operational planning of a large-scale industrial batch plant typically occurs over a time horizon of several months with the goal of providing daily production targets and raw material requirements for the plant in question. Due to the length of the time horizon, demand uncertainty should be taken into account in order to ensure that the operational planning model provides reliable production targets and/or raw material requirements. A robust novel operational planning model has been developed in order to address the objective of providing a reliable daily production profile which is immune to various forms of demand uncertainty. The ability of the proposed planning model to address the aforementioned objectives of an operational planning model has been validated through an industrial case study of a large-scale, multiproduct, and multipurpose batch plant having the capability of producing hundreds of different products over a time horizon of three months. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9001124

Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty / Peter M. Verderame in Industrial & engineering chemistry research, Vol. 49 N° 1 (Janvier 2010) 

Permalink

Planning and scheduling under uncertainty / Peter M. Verderame in Industrial & engineering chemistry research, Vol. 49 N° 9 (Mai 2010) 

Permalink