Documents disponibles écrits par cet auteur

Rolling horizon approach for dynamic parallel machine scheduling problem with release times / Lixin Tang in Industrial & engineering chemistry research, Vol. 49 N° 1 (Janvier 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 1 (Janvier 2010) . - pp. 381–389 Titre : Rolling horizon approach for dynamic parallel machine scheduling problem with release times Type de document : texte imprimé Auteurs : Lixin Tang, Auteur ; Shujun Jiang, Auteur ; Jiyin Liu, Auteur Année de publication : 2010 Article en page(s) : pp. 381–389 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Rolling  Horizon  Approach  for  Dynamic  Parallel  Machine  Scheduling  Problem  with  Release  Times Résumé : In this paper, we study a dynamic parallel machine scheduling problem with release times, where the release times and processing times of jobs may change during the production process due to uncertainties. The problem is different from classical scheduling problems in the deterministic environment where all information of jobs is known at the beginning of the scheduling horizon and will not change during the operations throughout the whole horizon. In practice, there are often unpredictable events causing dynamic changes in job release times and/or processing times. Traditional optimization methods cannot solve the dynamic scheduling problem directly even though they have been successful in solving the static version of the problem. A model predictive control (MPC) strategy based rolling horizon approach is applied to tackle the dynamic parallel machine scheduling problem with the objective of minimizing the total weighted completion times of jobs, the energy consumption due to job waiting, and the total deviation of actual job completion times from those in the original schedule. When the MPC is applied to the problem, the rolling horizon approach allows applying a Lagrangian relaxation (LR) algorithm to solve the model of the scheduling problem in a rolling fashion. Computational experiments are carried out comparing the proposed method with the passive adjustment method often adopted by human schedulers. The result shows that the proposed method yields significantly better results, with 11.72% improvement on average. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900206m [article] Rolling horizon approach for dynamic parallel machine scheduling problem with release times [texte imprimé] / Lixin Tang, Auteur ; Shujun Jiang, Auteur ; Jiyin Liu, Auteur . - 2010 . - pp. 381–389. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 1 (Janvier 2010) . - pp. 381–389 Mots-clés : Rolling  Horizon  Approach  for  Dynamic  Parallel  Machine  Scheduling  Problem  with  Release  Times Résumé : In this paper, we study a dynamic parallel machine scheduling problem with release times, where the release times and processing times of jobs may change during the production process due to uncertainties. The problem is different from classical scheduling problems in the deterministic environment where all information of jobs is known at the beginning of the scheduling horizon and will not change during the operations throughout the whole horizon. In practice, there are often unpredictable events causing dynamic changes in job release times and/or processing times. Traditional optimization methods cannot solve the dynamic scheduling problem directly even though they have been successful in solving the static version of the problem. A model predictive control (MPC) strategy based rolling horizon approach is applied to tackle the dynamic parallel machine scheduling problem with the objective of minimizing the total weighted completion times of jobs, the energy consumption due to job waiting, and the total deviation of actual job completion times from those in the original schedule. When the MPC is applied to the problem, the rolling horizon approach allows applying a Lagrangian relaxation (LR) algorithm to solve the model of the scheduling problem in a rolling fashion. Computational experiments are carried out comparing the proposed method with the passive adjustment method often adopted by human schedulers. The result shows that the proposed method yields significantly better results, with 11.72% improvement on average. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900206m

The charge batching planning problem in steelmaking process using lagrangian relaxation algorithm / Lixin Tang in Industrial & engineering chemistry research, Vol. 48 N° 16 (Août 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 16 (Août 2009) . - pp. 7780–7787 Titre : The charge batching planning problem in steelmaking process using lagrangian relaxation algorithm Type de document : texte imprimé Auteurs : Lixin Tang, Auteur ; Shujun Jiang, Auteur Année de publication : 2009 Article en page(s) : pp. 7780–7787 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Charge  batching  planning  problem  Steelmaking  processing  Lagrangian  relaxation  methods Résumé : In this paper, we investigate the charge batching planning problem (CBP) arising from practical steelmaking production. The CBP transforms the primary order requirements into various production batches (charges) subject to the steelmaking processing constraints and composite batch conditions according to the similarity in steelgrade, dimension, physical property, and due-date of orders. On the basis of a practical steelmaking process, a novel mixed-integer programming model for the CBP is presented by considering above constraints and features here, and two kinds of Lagrangian relaxation (LR) methods are proposed to solve the CBP by using different relaxation methods. In the first LR method, the relaxed problem is separated into subproblems by relaxing assignment constraints which are solved optimally by dynamic programming. In the second method, variable splitting is presented by introducing identical copies of some subsets of the original variables. To guarantee the equivalence to the primal problem, a number of equality coupling constraints are added into the model which are relaxed during the course of the second Lagangian relaxation. The multipliers in all above LR methods are then iteratively updated along subgradient directions. Computational experiments have been carried out and the results show that both LR methods can produce satisfactory average duality gaps and the second LR method is little better than the first method. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801454k [article] The charge batching planning problem in steelmaking process using lagrangian relaxation algorithm [texte imprimé] / Lixin Tang, Auteur ; Shujun Jiang, Auteur . - 2009 . - pp. 7780–7787. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 16 (Août 2009) . - pp. 7780–7787 Mots-clés : Charge  batching  planning  problem  Steelmaking  processing  Lagrangian  relaxation  methods Résumé : In this paper, we investigate the charge batching planning problem (CBP) arising from practical steelmaking production. The CBP transforms the primary order requirements into various production batches (charges) subject to the steelmaking processing constraints and composite batch conditions according to the similarity in steelgrade, dimension, physical property, and due-date of orders. On the basis of a practical steelmaking process, a novel mixed-integer programming model for the CBP is presented by considering above constraints and features here, and two kinds of Lagrangian relaxation (LR) methods are proposed to solve the CBP by using different relaxation methods. In the first LR method, the relaxed problem is separated into subproblems by relaxing assignment constraints which are solved optimally by dynamic programming. In the second method, variable splitting is presented by introducing identical copies of some subsets of the original variables. To guarantee the equivalence to the primal problem, a number of equality coupling constraints are added into the model which are relaxed during the course of the second Lagangian relaxation. The multipliers in all above LR methods are then iteratively updated along subgradient directions. Computational experiments have been carried out and the results show that both LR methods can produce satisfactory average duality gaps and the second LR method is little better than the first method. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801454k