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Rezg Nidhal - One of the best experts on this subject based on the ideXlab platform.

  • an optimal mathematical modeling for manufacturing remanufacturing problem under carbon emission constraint
    International Conference on Modeling Simulation and Applied Optimization, 2017
    Co-Authors: Bouslikhane Salim, Hajej Zied, Rezg Nidhal
    Abstract:

    This paper proposes a mathematical model for a manufacturing and remanufacturing production problem which integrates environmental constraint. This study deals a closedloop system composed by a manufacturing and remanufacturing machines subject to Random failures, in order to satisfy the Random Demand. This paper proposed two mathematical model minimizing the total cost of production, inventory and maintenance taking into account the given maintenance plan for the remanufacturing machine and respecting the emission tax constraint. The principle objective is to determine the economical production plans of manufacturing and remanufacturing machines and the quantity of emission carbon for each production period. The key of this study is to take into account the influence of the variation of production rates on the failure rate of manufacturing system.

  • joint optimisation of maintenance and production policies considering Random Demand and variable production rate
    International Journal of Production Research, 2012
    Co-Authors: Souheil Ayed, Dellagi Sofiene, Rezg Nidhal
    Abstract:

    This paper deals with a Randomly failing manufacturing system M1 which has to satisfy a Random Demand during a finite horizon given a required service level. To help meet this Demand, subcontracting is used through another production system M2. M1 operates with a variable production rate and its failure rate depends on both time and the production rate. In these conditions, as a first step, we establish a preliminary production plan corresponding to a given service level. In a second stage, we integrate the effect of the machine degradation introducing a unitary degradation cost. The optimal production plan is then obtained by minimising the sum of the production, the inventory and the degradation costs. In the final stage, we propose another optimal plan combined with a preventive maintenance policy aiming at reducing the machine degradation while minimising the total cost including the production, inventory and maintenance costs.

  • optimal integrated maintenance production policy for Randomly failing systems with variable failure rate
    International Journal of Production Research, 2011
    Co-Authors: Hajej Zied, Dellagi Sofiene, Rezg Nidhal
    Abstract:

    This article deals with the combined production and maintenance plans for a manufacturing system satisfying a Random Demand. We first establish an optimal production plan which minimises the average total inventory and production cost. Second, using this optimal production plan, and taking into account the deterioration of the machine according to its production rate, we derive an optimal maintenance schedule which minimises the maintenance cost. A numerical example illustrates the proposed approach, this analytical approach, based on a stochastic optimisation model and using the operational age concept, reveals the significant influence of the production rate on the deterioration of the manufacturing system and consequently on the integrated production/maintenance policy.

  • an optimal maintenance production planning for a manufacturing system under Random failure rate and a subcontracting constraint
    2011
    Co-Authors: Hajej Zied, Dellagi Sofiene, Rezg Nidhal
    Abstract:

    This paper deals with a problem of production and maintenance of manufacturing system under subcontracting constraint. We have developed an integrated production/maintenance policy for a manufacturing system subjected to a Random failure and calling up on subcontractor machine. The problem consists on a machine, unable to satisfy a Random Demand. That’s why it called upon another machine. In order to assure simultaneously an economical production planning and optimal maintenance strategy, a conjoint optimization is made which minimize the total production, holding and maintenance cost. An analytical study and a numerical example are presented in order to prove the developed approach.

  • production maintenance policies optimization with operational age concept in a subcontracting constraint
    IFAC Proceedings Volumes, 2011
    Co-Authors: Hajej Zied, Dellagi Sofiene, Rezg Nidhal
    Abstract:

    Abstract In this paper, we deal with the problem of a joint maintenance and production policy under a subcontracting constraint. In fact, this paper is the continuity of our previous work. The manufacturing system under consideration consists of a machine M that produces a single product. To satisfy a Random Demand d under a given service level constraint, the system called upon another machine M 2 (the subcontractor) which recycles and remanufactures the products rejected by the customer. We first establish an optimal production plan which minimizes the total inventory and production cost taking into consideration the subcontractor constraint. Secondly, using this optimal production plan and based on the operational age concept, we derive an optimal maintenance schedule which minimizes the total maintenance cost. Finally, a numerical example is studied in order to apply the developed approach.

Jan A Van Mieghem - One of the best experts on this subject based on the ideXlab platform.

  • global dual sourcing tailored base surge allocation to near and offshore production
    2010
    Co-Authors: Gad Allon, Jan A Van Mieghem
    Abstract:

    When designing a sourcing strategy in practice, a key task is to determine the average order rates placed to each source because that affects costs and supplier management. We consider a firm that has access to a responsive near-shore source (e.g., Mexico) and a low-cost offshore source (e.g., China). The firm must determine an inventory sourcing policy to satisfy Random Demand over time. Unfortunately, the optimal policy is too complex to allow a direct answer to our key question. Therefore, we analyze a tailored base-surge (TBS) sourcing policy that is simple, used in practice, and captures the classic trade-off between cost and responsiveness. The TBS policy combines push and pull controls by replenishing at a constant rate from the offshore source and producing at the nearshore plant only when inventory is below a target. The constant base allocation allows the offshore facility to focus on cost efficiency, whereas the nearshore facility's quick response capability is utilized only dynamically to guarantee high service. The research goals are to (i) determine the allocation of Random Demand into base and surge capacity, (ii) estimate the corresponding working capital requirements, and (iii) identify and value the key drivers of dual sourcing. We present performance bounds on the optimal cost and prove that economic optimization brings the system into heavy traffic. We analyze the sourcing policy that is asymptotically optimal for high-volume systems and present a simple "square-root" formula that is insightful to answer our questions and sufficiently accurate for practice, as is demonstrated with a validation study.

  • global dual sourcing tailored base surge allocation to near and offshore production
    Management Science, 2010
    Co-Authors: Gad Allon, Jan A Van Mieghem
    Abstract:

    When designing a sourcing strategy in practice, a key task is to determine the average order rates placed to each source because that affects cost and supplier management. We consider a firm that has access to a responsive nearshore source (e.g., Mexico) and a low-cost offshore source (e.g., China). The firm must determine an inventory sourcing policy to satisfy Random Demand over time. Unfortunately, the optimal policy is too complex to allow a direct answer to our key question. Therefore, we analyze a tailored base-surge (TBS) sourcing policy that is simple, used in practice, and captures the classic trade-off between cost and responsiveness. The TBS policy combines push and pull controls by replenishing at a constant rate from the offshore source and producing at the nearshore plant only when inventory is below a target. The constant base allocation allows the offshore facility to focus on cost efficiency, whereas the nearshore facility's quick response capability is utilized only dynamically to guarantee high service. The research goals are to (i) determine the allocation of Random Demand into base and surge capacity, (ii) estimate corresponding working capital requirements, and (iii) identify and value the key drivers of dual sourcing. We present performance bounds on the optimal cost and prove that economic optimization brings the system into heavy traffic. We analyze the sourcing policy that is asymptotically optimal for high-volume systems and present a simple “square-root” formula that is insightful to answer our questions and sufficiently accurate for practice, as is demonstrated with a validation study.

Horst Tempelmeier - One of the best experts on this subject based on the ideXlab platform.

  • a column generation heuristic for dynamic capacitated lot sizing with Random Demand under a fill rate constraint
    Omega-international Journal of Management Science, 2011
    Co-Authors: Horst Tempelmeier
    Abstract:

    This paper deals with the dynamic multi-item capacitated lot-sizing problem under Random period Demands (SCLSP). Unfilled Demands are backordered and a fill rate constraint is in effect. It is assumed that, according to the static-uncertainty strategy of Bookbinder and Tan [1], all decisions concerning the time and the production quantities are made in advance for the entire planning horizon regardless of the realization of the Demands. The problem is approximated with the set partitioning model and a heuristic solution procedure that combines column generation and the recently developed ABC[beta] heuristic is proposed.

  • dynamic uncapacitated lot sizing with Random Demand under a fillrate constraint
    European Journal of Operational Research, 2011
    Co-Authors: Horst Tempelmeier, Sascha Herpers
    Abstract:

    This paper deals with the single-item dynamic uncapacitated lot sizing problem with Random Demand. We propose a model based on the "static uncertainty" strategy of Bookbinder and Tan (1988). In contrast to these authors, we use exact expressions for the inventory costs and we apply a fillrate constraint. We present an exact solution method and modify several well-known dynamic lot sizing heuristics such that they can be applied for the case of dynamic stochastic Demands. A numerical experiment shows that there are significant differences in the performance of the heuristics whereat the ranking of the heuristics is different from that reported for the case of deterministic Demand.

  • a column generation heuristic for dynamic capacitated lot sizing with Random Demand under a fillrate constraint
    Industrial Engineering and Engineering Management, 2010
    Co-Authors: Horst Tempelmeier
    Abstract:

    This paper deals with the dynamic multi-item capacitated lot-sizing problem under Random period Demands (SCLSP). Unfilled Demands are backordered and a fillrate constraint is in effect. It is assumed that, according to the static-uncertainty strategy of Bookbinder and Tan (1988), all decisions concerning the time and the production quantities are made in advance for the entire planning horizon regardless of the realization of the Demands. The problem is approximated with the set partitioning model and a heuristic solution procedure that combines column generation and the recently developed ABC β heuristic is proposed.

  • abcβ a heuristic for dynamic capacitated lot sizing with Random Demand under a fill rate constraint
    International Journal of Production Research, 2010
    Co-Authors: Horst Tempelmeier, Sascha Herpers
    Abstract:

    This paper deals with the dynamic multi-item capacitated lot-sizing problem (CLSP) with Random Demand over a finite discrete time horizon. Unfilled Demands are backordered. It is assumed that a fill rate constraint is in effect. We propose a heuristic solution procedure called ABC β that extends the A/B/C heuristic introduced by Maes and Van Wassenhove for the deterministic CLSP to the case of Random Demands.

Gad Allon - One of the best experts on this subject based on the ideXlab platform.

  • global dual sourcing tailored base surge allocation to near and offshore production
    2010
    Co-Authors: Gad Allon, Jan A Van Mieghem
    Abstract:

    When designing a sourcing strategy in practice, a key task is to determine the average order rates placed to each source because that affects costs and supplier management. We consider a firm that has access to a responsive near-shore source (e.g., Mexico) and a low-cost offshore source (e.g., China). The firm must determine an inventory sourcing policy to satisfy Random Demand over time. Unfortunately, the optimal policy is too complex to allow a direct answer to our key question. Therefore, we analyze a tailored base-surge (TBS) sourcing policy that is simple, used in practice, and captures the classic trade-off between cost and responsiveness. The TBS policy combines push and pull controls by replenishing at a constant rate from the offshore source and producing at the nearshore plant only when inventory is below a target. The constant base allocation allows the offshore facility to focus on cost efficiency, whereas the nearshore facility's quick response capability is utilized only dynamically to guarantee high service. The research goals are to (i) determine the allocation of Random Demand into base and surge capacity, (ii) estimate the corresponding working capital requirements, and (iii) identify and value the key drivers of dual sourcing. We present performance bounds on the optimal cost and prove that economic optimization brings the system into heavy traffic. We analyze the sourcing policy that is asymptotically optimal for high-volume systems and present a simple "square-root" formula that is insightful to answer our questions and sufficiently accurate for practice, as is demonstrated with a validation study.

  • global dual sourcing tailored base surge allocation to near and offshore production
    Management Science, 2010
    Co-Authors: Gad Allon, Jan A Van Mieghem
    Abstract:

    When designing a sourcing strategy in practice, a key task is to determine the average order rates placed to each source because that affects cost and supplier management. We consider a firm that has access to a responsive nearshore source (e.g., Mexico) and a low-cost offshore source (e.g., China). The firm must determine an inventory sourcing policy to satisfy Random Demand over time. Unfortunately, the optimal policy is too complex to allow a direct answer to our key question. Therefore, we analyze a tailored base-surge (TBS) sourcing policy that is simple, used in practice, and captures the classic trade-off between cost and responsiveness. The TBS policy combines push and pull controls by replenishing at a constant rate from the offshore source and producing at the nearshore plant only when inventory is below a target. The constant base allocation allows the offshore facility to focus on cost efficiency, whereas the nearshore facility's quick response capability is utilized only dynamically to guarantee high service. The research goals are to (i) determine the allocation of Random Demand into base and surge capacity, (ii) estimate corresponding working capital requirements, and (iii) identify and value the key drivers of dual sourcing. We present performance bounds on the optimal cost and prove that economic optimization brings the system into heavy traffic. We analyze the sourcing policy that is asymptotically optimal for high-volume systems and present a simple “square-root” formula that is insightful to answer our questions and sufficiently accurate for practice, as is demonstrated with a validation study.

Sascha Herpers - One of the best experts on this subject based on the ideXlab platform.

  • dynamic uncapacitated lot sizing with Random Demand under a fillrate constraint
    European Journal of Operational Research, 2011
    Co-Authors: Horst Tempelmeier, Sascha Herpers
    Abstract:

    This paper deals with the single-item dynamic uncapacitated lot sizing problem with Random Demand. We propose a model based on the "static uncertainty" strategy of Bookbinder and Tan (1988). In contrast to these authors, we use exact expressions for the inventory costs and we apply a fillrate constraint. We present an exact solution method and modify several well-known dynamic lot sizing heuristics such that they can be applied for the case of dynamic stochastic Demands. A numerical experiment shows that there are significant differences in the performance of the heuristics whereat the ranking of the heuristics is different from that reported for the case of deterministic Demand.

  • abcβ a heuristic for dynamic capacitated lot sizing with Random Demand under a fill rate constraint
    International Journal of Production Research, 2010
    Co-Authors: Horst Tempelmeier, Sascha Herpers
    Abstract:

    This paper deals with the dynamic multi-item capacitated lot-sizing problem (CLSP) with Random Demand over a finite discrete time horizon. Unfilled Demands are backordered. It is assumed that a fill rate constraint is in effect. We propose a heuristic solution procedure called ABC β that extends the A/B/C heuristic introduced by Maes and Van Wassenhove for the deterministic CLSP to the case of Random Demands.