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Entropy-based optimization of decentralized supply-chain networks / T. Sundar Raj in Industrial & engineering chemistry research, Vol. 49 N° 7 (Avril 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 7 (Avril 2010) . - pp. 3250–3261 Titre : Entropy-based optimization of decentralized supply-chain networks Type de document : texte imprimé Auteurs : T. Sundar Raj, Auteur ; S. Lakshminarayanan, Auteur Année de publication : 2010 Article en page(s) : pp. 3250–3261 Note générale : Industrial Chemistry Langues : Anglais (eng) Mots-clés : Entropy  Optimization  Decentralized  Supply  Chain  Networks Résumé : Supply-chain operations are intricate and complex due to exogenous and endogenous uncertainties. The prime weakness in a decentralized supply chain arises due to lack of consideration of the uncertainty generation and transmission between supply-chain entities. Ineffective internal strategies carry the uncertainties beyond the boundaries of the supply-chain entity and consequently affect predictability of supply-chain behavior, customer satisfaction, and cost. Previous attempts made to enhance the supply-chain performance by optimizing the replenishment strategy do not pay attention to the issue of increasing uncertainty and consequent operational complexity in the system. The storage and flow of uncertainty must therefore be controlled and managed effectively. The minimization of complexity in supply chains using Shannon’s entropy-based measures by tweaking supply-chain decision parameters (replenishment parameters) is a unique aspect of this work. As a result, the predictability of the supply chain is improved. Four complexity management strategies (S-I to S-IV) are proposed and analyzed to understand their benefits under diverse business scenarios. Our investigations demonstrate that the strategy which aims to minimize an additive measure of information and material flow complexity outperforms other complexity management strategies under all business scenarios. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9003688 [article] Entropy-based optimization of decentralized supply-chain networks [texte imprimé] / T. Sundar Raj, Auteur ; S. Lakshminarayanan, Auteur . - 2010 . - pp. 3250–3261. Industrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 7 (Avril 2010) . - pp. 3250–3261 Mots-clés : Entropy  Optimization  Decentralized  Supply  Chain  Networks Résumé : Supply-chain operations are intricate and complex due to exogenous and endogenous uncertainties. The prime weakness in a decentralized supply chain arises due to lack of consideration of the uncertainty generation and transmission between supply-chain entities. Ineffective internal strategies carry the uncertainties beyond the boundaries of the supply-chain entity and consequently affect predictability of supply-chain behavior, customer satisfaction, and cost. Previous attempts made to enhance the supply-chain performance by optimizing the replenishment strategy do not pay attention to the issue of increasing uncertainty and consequent operational complexity in the system. The storage and flow of uncertainty must therefore be controlled and managed effectively. The minimization of complexity in supply chains using Shannon’s entropy-based measures by tweaking supply-chain decision parameters (replenishment parameters) is a unique aspect of this work. As a result, the predictability of the supply chain is improved. Four complexity management strategies (S-I to S-IV) are proposed and analyzed to understand their benefits under diverse business scenarios. Our investigations demonstrate that the strategy which aims to minimize an additive measure of information and material flow complexity outperforms other complexity management strategies under all business scenarios. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9003688

Multiobjective optimization in multiechelon decentralized supply chains / T. Sundar Raj in Industrial & engineering chemistry research, Vol. 47 N°17 (Septembre 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6661–6671 Titre : Multiobjective optimization in multiechelon decentralized supply chains Type de document : texte imprimé Auteurs : T. Sundar Raj, Auteur ; S. Lakshminarayanan, Auteur Année de publication : 2008 Article en page(s) : p. 6661–6671 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Supply  chains  Multiobjective  fashion  Multiobjective  optimization  Hyper-space  diagonal  counting  method Résumé : Supply chain is a collaborative strategy between raw material vendors, manufacturers, and finished product distributors. It aims for synchronized material, information, and financial flows within the internal components of the supply chain to leverage an effective business outcome. The performance of a supply chain is governed by inventory (resources) minimization and order fill-rate (output) maximization. Any performance improvement in real world supply chains could lead to substantial gain in customer service levels and profit margins, thereby adding to its competitive edge over rival supply chains. This may be achieved by revising the tactical decisions to leverage both internal and external entities of the network and utilizing bullwhip as a beneficial constraint. The present work attempts to improve supply chain performance in a multiobjective fashion using multiobjective optimization. A hyper-space diagonal counting method is employed to process the Pareto front and locate an implementable solution. The workability of this multiobjective performance enhancement approach and the Pareto analysis to identify the right decision are demonstrated using a case study that takes into consideration the different business strategies adopted by supply chains. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800153z [article] Multiobjective optimization in multiechelon decentralized supply chains [texte imprimé] / T. Sundar Raj, Auteur ; S. Lakshminarayanan, Auteur . - 2008 . - p. 6661–6671. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6661–6671 Mots-clés : Supply  chains  Multiobjective  fashion  Multiobjective  optimization  Hyper-space  diagonal  counting  method Résumé : Supply chain is a collaborative strategy between raw material vendors, manufacturers, and finished product distributors. It aims for synchronized material, information, and financial flows within the internal components of the supply chain to leverage an effective business outcome. The performance of a supply chain is governed by inventory (resources) minimization and order fill-rate (output) maximization. Any performance improvement in real world supply chains could lead to substantial gain in customer service levels and profit margins, thereby adding to its competitive edge over rival supply chains. This may be achieved by revising the tactical decisions to leverage both internal and external entities of the network and utilizing bullwhip as a beneficial constraint. The present work attempts to improve supply chain performance in a multiobjective fashion using multiobjective optimization. A hyper-space diagonal counting method is employed to process the Pareto front and locate an implementable solution. The workability of this multiobjective performance enhancement approach and the Pareto analysis to identify the right decision are demonstrated using a case study that takes into consideration the different business strategies adopted by supply chains. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800153z