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Robust optimization model for crude oil scheduling under uncertainty / Wang, Jishuai in Industrial & engineering chemistry research, Vol. 49 N° 4 (Fevrier 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1737–1748 Titre : Robust optimization model for crude oil scheduling under uncertainty Type de document : texte imprimé Auteurs : Wang, Jishuai, Auteur ; Rong, Gang, Auteur Année de publication : 2010 Article en page(s) : pp 1737–1748 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Crude  oil  Optimization. Résumé : In this article, a two-stage robust model is proposed to solve the crude oil scheduling problem under uncertain conditions. The first stage of the model is developed using chance-constrained programming and fuzzy programming that can be transformed into the deterministic counterpart problem, whereas the second-stage is scenario-based. Through the combination of the approaches, the two-stage model can deal with uncertain parameters with both continuous and discrete probability distributions within a finite number of scenarios. The model was tested on several small examples and an industrial-size case. Uncertainties were introduced in ship arrival times and fluctuating product demands. The computational results demonstrate the effectiveness and robustness of the proposed approach. The tradeoff between solution robustness and model robustness was also analyzed. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900358z [article] Robust optimization model for crude oil scheduling under uncertainty [texte imprimé] / Wang, Jishuai, Auteur ; Rong, Gang, Auteur . - 2010 . - pp 1737–1748. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1737–1748 Mots-clés : Crude  oil  Optimization. Résumé : In this article, a two-stage robust model is proposed to solve the crude oil scheduling problem under uncertain conditions. The first stage of the model is developed using chance-constrained programming and fuzzy programming that can be transformed into the deterministic counterpart problem, whereas the second-stage is scenario-based. Through the combination of the approaches, the two-stage model can deal with uncertain parameters with both continuous and discrete probability distributions within a finite number of scenarios. The model was tested on several small examples and an industrial-size case. Uncertainties were introduced in ship arrival times and fluctuating product demands. The computational results demonstrate the effectiveness and robustness of the proposed approach. The tradeoff between solution robustness and model robustness was also analyzed. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900358z