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Détail de l'auteur
Auteur Kailiang Tong
Documents disponibles écrits par cet auteur
Affiner la recherchePlanning under Demand and Yield Uncertainties in an Oil Supply Chain / Kailiang Tong in Industrial & engineering chemistry research, Vol. 51 N° 2 (Janvier 2012)
[article]
in Industrial & engineering chemistry research > Vol. 51 N° 2 (Janvier 2012) . - pp. 814-834
Titre : Planning under Demand and Yield Uncertainties in an Oil Supply Chain Type de document : texte imprimé Auteurs : Kailiang Tong, Auteur ; Yiping Feng, Auteur Année de publication : 2012 Article en page(s) : pp. 814-834 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Uncertainty Planning Résumé : In this article, a stochastic programming approach for an optimal refinery planning problem under uncertainties is proposed. The nominal planning model is extended by means of conditional value-at-risk theory. Demand amount uncertainty and product yield fluctuation are taken into account simultaneously. The risk of customer dissatisfaction and inventory violation are considered as constraints according to the decision maker's risk tolerance. Sample average approximation approach is employed to test the robustness of the model and determine the suitable risk aversion value. A more accurate product yield distribution based upon a Markov chain is introduced and applied in this model. A problem with such endogenous uncertainty is solved using a heuristic iterative algorithm integrating stochastic programming and simulation framework. Also, the scenario number in the stochastic programming model is determined by a statistical analysis, which is a compromise of model accuracy and problem size. At the end of this article, a comprehensive analysis is presented to illustrate the effectiveness of the proposed model. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25476416 [article] Planning under Demand and Yield Uncertainties in an Oil Supply Chain [texte imprimé] / Kailiang Tong, Auteur ; Yiping Feng, Auteur . - 2012 . - pp. 814-834.
Chimie industrielle
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 51 N° 2 (Janvier 2012) . - pp. 814-834
Mots-clés : Uncertainty Planning Résumé : In this article, a stochastic programming approach for an optimal refinery planning problem under uncertainties is proposed. The nominal planning model is extended by means of conditional value-at-risk theory. Demand amount uncertainty and product yield fluctuation are taken into account simultaneously. The risk of customer dissatisfaction and inventory violation are considered as constraints according to the decision maker's risk tolerance. Sample average approximation approach is employed to test the robustness of the model and determine the suitable risk aversion value. A more accurate product yield distribution based upon a Markov chain is introduced and applied in this model. A problem with such endogenous uncertainty is solved using a heuristic iterative algorithm integrating stochastic programming and simulation framework. Also, the scenario number in the stochastic programming model is determined by a statistical analysis, which is a compromise of model accuracy and problem size. At the end of this article, a comprehensive analysis is presented to illustrate the effectiveness of the proposed model. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25476416