Documents disponibles écrits par cet auteur

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

Genetic programming based variable interaction models for classification of process and biological systems / Raghuraj K. Rao in Industrial & engineering chemistry research, Vol. 48 N° 10 (Mai 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 10 (Mai 2009) . - pp. 4899–4907 Titre : Genetic programming based variable interaction models for classification of process and biological systems Type de document : texte imprimé Auteurs : Raghuraj K. Rao, Auteur ; Kyaw Tun, Auteur ; S. Lakshminarayanan, Auteur Année de publication : 2009 Article en page(s) : pp. 4899–4907 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Genetic  programming  Variable  dependency  models  Linear  classification  Nonlinear  classification Résumé : Classification of data originating from complex process and biological systems is challenging owing to the presence of multivariate and highly nonlinear interactions between variables. Patterns, difficult to distinguish using decision boundaries or available discriminating rules, can be separated based on unique inter-relations among the feature vectors. Given the complex nature of such systems, the variable interaction models are difficult to establish. Genetic programming (GP), a data-driven evolutionary modeling approach, is suggested here to be a potential tool for designing variable dependency models and exploiting them further for class discriminant analysis. Thus, this paper proposes a new GP model based classification approach. The approach is applied on illustrative data sets, and its performance is benchmarked against well-established linear and nonlinear classifiers such as LDA, kNN, CART, ANN, and SVM. It is demonstrated that GP based models can play an effective role in classification of data into multiple classes. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801147m [article] Genetic programming based variable interaction models for classification of process and biological systems [texte imprimé] / Raghuraj K. Rao, Auteur ; Kyaw Tun, Auteur ; S. Lakshminarayanan, Auteur . - 2009 . - pp. 4899–4907. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 10 (Mai 2009) . - pp. 4899–4907 Mots-clés : Genetic  programming  Variable  dependency  models  Linear  classification  Nonlinear  classification Résumé : Classification of data originating from complex process and biological systems is challenging owing to the presence of multivariate and highly nonlinear interactions between variables. Patterns, difficult to distinguish using decision boundaries or available discriminating rules, can be separated based on unique inter-relations among the feature vectors. Given the complex nature of such systems, the variable interaction models are difficult to establish. Genetic programming (GP), a data-driven evolutionary modeling approach, is suggested here to be a potential tool for designing variable dependency models and exploiting them further for class discriminant analysis. Thus, this paper proposes a new GP model based classification approach. The approach is applied on illustrative data sets, and its performance is benchmarked against well-established linear and nonlinear classifiers such as LDA, kNN, CART, ANN, and SVM. It is demonstrated that GP based models can play an effective role in classification of data into multiple classes. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801147m

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

A new unified approach to valve stiction quantification and compensation / Lee Zhi Xiang Ivan in Industrial & engineering chemistry research, Vol. 48 N° 7 (Avril 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 7 (Avril 2009) . - pp. 3474–3483 Titre : A new unified approach to valve stiction quantification and compensation Type de document : texte imprimé Auteurs : Lee Zhi Xiang Ivan, Auteur ; S. Lakshminarayanan, Auteur Année de publication : 2009 Article en page(s) : pp. 3474–3483 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Valve  stiction  Control  loops  Hammerstein  identification  approach Résumé : Satisfactory control loop performance has always been a vital objective in process industries for economic reasons. However, unsatisfactory performance may prevail, of which valve stiction is a common culprit. In this work, a new unified approach is introduced to quantify valve stiction in control loops and then compensate for it. The newly proposed stiction quantification method uses a one-parameter stiction model and is based on a modified Hammerstein identification approach. In conjunction with the stiction quantification algorithm, a novel compensation technique that adds a constant amplitude signal to the valve input signal is presented. The effectiveness of the proposed scheme is demonstrated using simulation examples. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800961f [article] A new unified approach to valve stiction quantification and compensation [texte imprimé] / Lee Zhi Xiang Ivan, Auteur ; S. Lakshminarayanan, Auteur . - 2009 . - pp. 3474–3483. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 7 (Avril 2009) . - pp. 3474–3483 Mots-clés : Valve  stiction  Control  loops  Hammerstein  identification  approach Résumé : Satisfactory control loop performance has always been a vital objective in process industries for economic reasons. However, unsatisfactory performance may prevail, of which valve stiction is a common culprit. In this work, a new unified approach is introduced to quantify valve stiction in control loops and then compensate for it. The newly proposed stiction quantification method uses a one-parameter stiction model and is based on a modified Hammerstein identification approach. In conjunction with the stiction quantification algorithm, a novel compensation technique that adds a constant amplitude signal to the valve input signal is presented. The effectiveness of the proposed scheme is demonstrated using simulation examples. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800961f

Optimal design of a rotating packed bed for VOC stripping from contaminated groundwater / Krishna Gudena in Industrial & engineering chemistry research, Vol. 51 N° 2 (Janvier 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 2 (Janvier 2012) . - pp. 835-847 Titre : Optimal design of a rotating packed bed for VOC stripping from contaminated groundwater Type de document : texte imprimé Auteurs : Krishna Gudena, Auteur ; G.P. Rangaiah, Auteur ; S. Lakshminarayanan, Auteur Année de publication : 2012 Article en page(s) : pp. 835-847 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Water  pollution  Ground  water  Stripping  Volatile  organic  compound  Packed  bed  Optimal  design Résumé : Groundwater pollution by volatile organic compounds (VOCs) is a serious environmental concern, and several techniques have been suggested and employed to strip off these harmful compounds. Since groundwater is classified as a distributed scale system, an efficient VOC stripping system should be portable and economically competitive. The focus of the current study is to remove trichloroethylene (TCE) from contaminated groundwater in a rotating packed bed (high gravity or HiGee). Although industrial applications of HiGee do exist, studies on optimal design of the same is scarce in the literature. The present study optimizes the design of an industrial-scale HiGee stripping process with conflicting objectives such as total annual cost (TAC) and total VOC removal under consideration. The synergy effect of heating and rotation is studied, and several inferences from this study are listed. Pareto-optimal solutions obtained provide a wide range of optimized design alternatives, one of which can be chosen and employed by the designers, as per their end needs. Component-wise power consumption, uncertainty analysis, and sensitivity analysis of the involved parameters and variables are also studied to provide further insights into the process. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25476417 [article] Optimal design of a rotating packed bed for VOC stripping from contaminated groundwater [texte imprimé] / Krishna Gudena, Auteur ; G.P. Rangaiah, Auteur ; S. Lakshminarayanan, Auteur . - 2012 . - pp. 835-847. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 2 (Janvier 2012) . - pp. 835-847 Mots-clés : Water  pollution  Ground  water  Stripping  Volatile  organic  compound  Packed  bed  Optimal  design Résumé : Groundwater pollution by volatile organic compounds (VOCs) is a serious environmental concern, and several techniques have been suggested and employed to strip off these harmful compounds. Since groundwater is classified as a distributed scale system, an efficient VOC stripping system should be portable and economically competitive. The focus of the current study is to remove trichloroethylene (TCE) from contaminated groundwater in a rotating packed bed (high gravity or HiGee). Although industrial applications of HiGee do exist, studies on optimal design of the same is scarce in the literature. The present study optimizes the design of an industrial-scale HiGee stripping process with conflicting objectives such as total annual cost (TAC) and total VOC removal under consideration. The synergy effect of heating and rotation is studied, and several inferences from this study are listed. Pareto-optimal solutions obtained provide a wide range of optimized design alternatives, one of which can be chosen and employed by the designers, as per their end needs. Component-wise power consumption, uncertainty analysis, and sensitivity analysis of the involved parameters and variables are also studied to provide further insights into the process. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25476417