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Global Capital/Total Annualized Cost Minimization of Homogeneous and Isothermal Reactor Networks / Wen Zhou in Industrial & engineering chemistry research, Vol. 47 N°10 (Mai 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N°10 (Mai 2008) . - p. 3771–3782 Titre : Global Capital/Total Annualized Cost Minimization of Homogeneous and Isothermal Reactor Networks Type de document : texte imprimé Auteurs : Wen Zhou, Auteur ; Vasilios I. Manousiouthakis, Auteur Année de publication : 2008 Article en page(s) : p. 3771–3782 Langues : Anglais (eng) Résumé : The minimum capital cost/total annualized cost (MCC/MTAC) problem is investigated, within the infinite-dimensional state-space (IDEAS) framework, for homogeneous and isothermal reactor networks. The resulting mathematical formulation is an infinite-dimensional program with linear constraints and a separable concave objective function to be minimized. The global optimum of this infinite program is approximated through global solution of a series of finite-dimensional programs with concave separable objective functions and linear feasible regions. A branch-and-bound algorithm is used to solve globally each of these finite programs. The proposed methodology is illustrated with a reactor network synthesis case study aiming at capital cost minimization. En ligne : https://pubs.acs.org/doi/abs/10.1021/ie060653%2B [article] Global Capital/Total Annualized Cost Minimization of Homogeneous and Isothermal Reactor Networks [texte imprimé] / Wen Zhou, Auteur ; Vasilios I. Manousiouthakis, Auteur . - 2008 . - p. 3771–3782. Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N°10 (Mai 2008) . - p. 3771–3782 Résumé : The minimum capital cost/total annualized cost (MCC/MTAC) problem is investigated, within the infinite-dimensional state-space (IDEAS) framework, for homogeneous and isothermal reactor networks. The resulting mathematical formulation is an infinite-dimensional program with linear constraints and a separable concave objective function to be minimized. The global optimum of this infinite program is approximated through global solution of a series of finite-dimensional programs with concave separable objective functions and linear feasible regions. A branch-and-bound algorithm is used to solve globally each of these finite programs. The proposed methodology is illustrated with a reactor network synthesis case study aiming at capital cost minimization. En ligne : https://pubs.acs.org/doi/abs/10.1021/ie060653%2B