Documents disponibles écrits par cet auteur

Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks / Fengqi You in Industrial & engineering chemistry research, Vol. 50 N° 17 (Septembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 10102-10127 Titre : Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks Type de document : texte imprimé Auteurs : Fengqi You, Auteur ; Belinda Wang, Auteur Année de publication : 2011 Article en page(s) : pp. 10102-10127 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Biomass  Optimization  Life  cycle  (environment) Résumé : This paper addresses the optimal design and planning of biomass-to-liquids (BTL) supply chains under economic and environmental criteria. The supply chain consists of multisite distributed-centralized processing networks for biomass conversion and liquid transportation fuel production. The economic objective is measured by the total annualized cost, and the measure of environmental performance is the life cycle greenhouse gas emissions. A multiobjective, multiperiod, mixed-integer linear programming model is proposed that takes into account diverse conversion pathways and technologies, feedstock seasonality, geographical diversity, biomass degradation, infrastructure compatibility, demand distribution, and government incentives. The model simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The problem is formulated as a bicriterion optimization model and solved with the ε-constraint method. The resulting Pareto-optimal curve reveals how the optimal annualized cost and the BTL processing network structure change with different environmental performances of the supply chain. The proposed approach is illustrated through a county-level case study for the state of Iowa. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483655 [article] Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks [texte imprimé] / Fengqi You, Auteur ; Belinda Wang, Auteur . - 2011 . - pp. 10102-10127. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 10102-10127 Mots-clés : Biomass  Optimization  Life  cycle  (environment) Résumé : This paper addresses the optimal design and planning of biomass-to-liquids (BTL) supply chains under economic and environmental criteria. The supply chain consists of multisite distributed-centralized processing networks for biomass conversion and liquid transportation fuel production. The economic objective is measured by the total annualized cost, and the measure of environmental performance is the life cycle greenhouse gas emissions. A multiobjective, multiperiod, mixed-integer linear programming model is proposed that takes into account diverse conversion pathways and technologies, feedstock seasonality, geographical diversity, biomass degradation, infrastructure compatibility, demand distribution, and government incentives. The model simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The problem is formulated as a bicriterion optimization model and solved with the ε-constraint method. The resulting Pareto-optimal curve reveals how the optimal annualized cost and the BTL processing network structure change with different environmental performances of the supply chain. The proposed approach is illustrated through a county-level case study for the state of Iowa. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483655

Mixed-integer Nonlinear programming models and algorithms for large-scale supply chain design with stochastic inventory management / Fengqi You in Industrial & engineering chemistry research, Vol. 47 N°20 (Octobre 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N°20 (Octobre 2008) . - P. 7802-7817 Titre : Mixed-integer Nonlinear programming models and algorithms for large-scale supply chain design with stochastic inventory management Type de document : texte imprimé Auteurs : Fengqi You, Auteur ; Ignacio E. Grossmann, Auteur Année de publication : 2008 Article en page(s) : P. 7802-7817 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Supply  chain  network  Mixed-integer  nonlinear  programming  (MINLP) Résumé : An important challenge for most chemical companies is to simultaneously consider inventory optimization and supply chain network design under demand uncertainty. This leads to a problem that requires integrating a stochastic inventory model with the supply chain network design model. This problem can be formulated as a large-scale combinatorial optimization model that includes nonlinear terms. Since these models are very difficult to solve, they require exploiting their properties and developing special solution techniques to reduce the computational effort. In this work, we analyze the properties of the basic model and develop solution techniques for a joint supply chain network design and inventory management model for a given product. The model is formulated as a nonlinear integer programming problem. By reformulating it as a mixed-integer nonlinear programming (MINLP) problem and using an associated convex relaxation model for initialization, we first propose a heuristic method to quickly obtain good-quality solutions. Further, a decomposition algorithm based on Lagrangean relaxation is developed for obtaining global or near-global optimal solutions. Extensive computational examples with up to 150 distribution centers and 150 retailers are presented to illustrate the performance of the algorithms and to compare them with the full-space solution. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800257x [article] Mixed-integer Nonlinear programming models and algorithms for large-scale supply chain design with stochastic inventory management [texte imprimé] / Fengqi You, Auteur ; Ignacio E. Grossmann, Auteur . - 2008 . - P. 7802-7817. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N°20 (Octobre 2008) . - P. 7802-7817 Mots-clés : Supply  chain  network  Mixed-integer  nonlinear  programming  (MINLP) Résumé : An important challenge for most chemical companies is to simultaneously consider inventory optimization and supply chain network design under demand uncertainty. This leads to a problem that requires integrating a stochastic inventory model with the supply chain network design model. This problem can be formulated as a large-scale combinatorial optimization model that includes nonlinear terms. Since these models are very difficult to solve, they require exploiting their properties and developing special solution techniques to reduce the computational effort. In this work, we analyze the properties of the basic model and develop solution techniques for a joint supply chain network design and inventory management model for a given product. The model is formulated as a nonlinear integer programming problem. By reformulating it as a mixed-integer nonlinear programming (MINLP) problem and using an associated convex relaxation model for initialization, we first propose a heuristic method to quickly obtain good-quality solutions. Further, a decomposition algorithm based on Lagrangean relaxation is developed for obtaining global or near-global optimal solutions. Extensive computational examples with up to 150 distribution centers and 150 retailers are presented to illustrate the performance of the algorithms and to compare them with the full-space solution. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800257x

Multisite capacity, production, and distribution planning with reactor modifications / Fengqi You 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. 4831-4849 Titre : Multisite capacity, production, and distribution planning with reactor modifications : MILP model, bilevel decomposition algorithm versus lagrangean decomposition scheme Type de document : texte imprimé Auteurs : Fengqi You, Auteur ; Ignacio E. Grossmann, Auteur ; John M. Wassick, Auteur Année de publication : 2011 Article en page(s) : pp. 4831-4849 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Mathematical  programming  Algorithm  Modeling  Mixed  integer  programming  Linear  programming  Reactor  Planning  Production Résumé : We propose a multiperiod mixed-integer linear programming (MILP) model for the simultaneous capacity, production, and distribution planning for a multisite system including a number of production sites and markets. Multiple products are produced in several production trains that are located in different sites. The unique feature of the proposed model is that it considers the construction times of capacity modifications and takes into account the option of capacity transformation by modifying the reactor in a production train from producing one product family to producing another one. To solve the resulting large-scale MLLP model, we present solution techniques based on Lagrangean decomposition and bilevel decomposition. Numerical examples are presented to illustrate the applicability of the model and the performance of the algorithms. It is shown that the bilevel decomposition is the superior solution approach in terms of faster computational times and smaller optimality gaps for the problem addressed in this work. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128618 [article] Multisite capacity, production, and distribution planning with reactor modifications : MILP model, bilevel decomposition algorithm versus lagrangean decomposition scheme [texte imprimé] / Fengqi You, Auteur ; Ignacio E. Grossmann, Auteur ; John M. Wassick, Auteur . - 2011 . - pp. 4831-4849. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 4831-4849 Mots-clés : Mathematical  programming  Algorithm  Modeling  Mixed  integer  programming  Linear  programming  Reactor  Planning  Production Résumé : We propose a multiperiod mixed-integer linear programming (MILP) model for the simultaneous capacity, production, and distribution planning for a multisite system including a number of production sites and markets. Multiple products are produced in several production trains that are located in different sites. The unique feature of the proposed model is that it considers the construction times of capacity modifications and takes into account the option of capacity transformation by modifying the reactor in a production train from producing one product family to producing another one. To solve the resulting large-scale MLLP model, we present solution techniques based on Lagrangean decomposition and bilevel decomposition. Numerical examples are presented to illustrate the applicability of the model and the performance of the algorithms. It is shown that the bilevel decomposition is the superior solution approach in terms of faster computational times and smaller optimality gaps for the problem addressed in this work. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128618