Mohsen Elhafsi - Academia.edu (original) (raw)
Papers by Mohsen Elhafsi
We consider the optimal control of an assemble-to-order (ATO) system with m components, a single ... more We consider the optimal control of an assemble-to-order (ATO) system with m components, a single end-product, and n customer classes. Demand from each class occurs continuously over time according to a Poisson process. Components are produced in separate production facilities, each with a finite production rate and exponentially distributed production times. Components can be stocked ahead of demand but incur
We consider an assembly system with multiple stages, multiple items, and multiple customer classe... more We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced in variable batch sizes, one batch at a time, with exponentially distributed batch production times. Demand from each class takes place continuously over time according to a compound Poisson process. At
We consider an assembly system with multiple stages, multiple items, and multiple customer classe... more We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced one unit at a time. To produce one unit of an item, one unit from each of its predecessor items is needed. Upon production completion, items are placed in inventory. At
OR Spektrum, 1996
In this paper, we study a manufacturing system consisting of two machines separated by two interm... more In this paper, we study a manufacturing system consisting of two machines separated by two intermediate buffers, and capable of producing two different products. Each product requires a constant processing time on each of the machines. Each machine requires a constant non-negligible setup change time from one product to the other. The demand rate for each product is considered to be piecewise constant. Each machine undergoes failure and repair. The time-to-failure and time-to-repair are exponentially distributed random variables. The setup change and processing operations are resumable. We model our system as a continuous time, continuous flow process. An optimal control problem is formulated for the system to minimize the total expected discounted cost over an infinite horizon. To determine the optimal control policy structure, a discrete version of the problem is solved numerically using a dynamic programming formulation with a piecewise linear penalty function. A real-time control algorithm is then developed with the objective of maintaining low work-in-process inventory and keeping the production close to the demand. The algorithm uses a hierarchical control structure to generate the loading times for each product on each machine in real time and to respond to random disruptions in the system. The system is simulated using this algorithm to study its performance. The performance of the algorithm is also compared to alternative policies.
Proceedings of the Fourth International Conference on Computer Integrated Manufacturing and Automation Technology, 1994
In this paper, we study the scheduling of a deterministic one-machine two-part-type setup system ... more In this paper, we study the scheduling of a deterministic one-machine two-part-type setup system under steady and transient conditions. The optimal solution, expressed as an optimal feedback control, provides the optimal production rates and setup switching epochs as a function of the state of the system. For the steady state, the optimal cyclic schedule is determined. For the transient case,
International Journal of Production Research, 2014
ABSTRACT This paper studies a single end product assemble-to-order system serving both the demand... more ABSTRACT This paper studies a single end product assemble-to-order system serving both the demand of the end product and the individual components. Demands are assumed to form independent Poisson streams with different rates. Unsatisfied demand, both for the end product and for components, is assumed lost and thus incurs a per unit lost sale penalty. The end product is assembled from K distinct components each produced on a different production facility (or procured from independent suppliers). Production lead times are non-identical and are assumed to be independent and exponentially distributed. Produced components are held in stock in anticipation of future demands. The goal is to determine the optimal component production and inventory allocation policy. The optimal policy is characterised using a Markov Decision Process model. It is shown that, in addition to the state-dependent threshold type, the optimal policy exhibits counter-intuitive features which have not been observed in systems without components demand. In particular, for certain combinations of system parameters, the optimal inventory allocation policy switches priority as the inventory level of components changes. Furthermore, for a particular component k, as the inventory level of other components increases, the desirability of satisfying Component k demand decreases. Finally, because in general the optimal policy is fairly complicated and is difficult to obtain numerically, due to the curse of dimensionality of dynamic programming, three heuristic policies are proposed. Extensive numerical experiments indicate that the three heuristics perform very well compared to the optimal policy.
Journal of Global Optimization, 1996
This paper deals with the optimal scheduling of a one-machine two-product manufacturing system wi... more This paper deals with the optimal scheduling of a one-machine two-product manufacturing system with setup, operating in a continuous time dynamic environment. The machine is reliable. A known constant setup time is incurred when switching over from a part to the other. Each part has specified constant processing time and constant demand rate, as well as an infinite supply of
Management Science, 2004
We consider the problem of allocating demand arising from N products to M production facilities w... more We consider the problem of allocating demand arising from N products to M production facilities with finite capacity and load-dependent manufacturing lead-times. Production facilities can choose to manufacture items either to-stock or to-order. If items are stocked, demand is satisfied immediately if there is on-hand inventory. Otherwise, demand is backlogged with the production facility to which it is assigned. Products
Production and Operations Management, 2009
Operations Research, 2011
Journal of Global Optimization, 1997
In this paper, we deal with the production scheduling ofseveral products that are produced period... more In this paper, we deal with the production scheduling ofseveral products that are produced periodically, in a fixed sequence, ona single machine. In the literature, this problem is usually referred to asthe Common Cycle Economic Lot Scheduling Problem. We extend thelatter to allow the production rates to be controllable at the beginningof as well as during each production run of a product. Also, we assumethat unsatisfied demand is completely backordered. The objective is todetermine the optimal schedule that satisfies the demand for all theproducts and that realizes the minimum average setup, inventoryholding and backlog cost per unit time. Comparison with previousresults (when production rates are fixed) reveals that averagecosts can be reduced up to 66% by allowing controllable productionrates.
Journal of Global Optimization, 1996
This paper deals with the optimal control of a one-machine two-product manufacturing system with ... more This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as
International Journal of Production Research, 2008
IEEE Transactions on Automation Science and Engineering, 2000
We consider a production-inventory system with two customer classes, one patient and one impatien... more We consider a production-inventory system with two customer classes, one patient and one impatient. Orders from the patient class can be backordered if needed, while orders from the impatient class must be rejected if they cannot be fulfilled from on-hand inventory. Orders backordered incur a backorder cost, while orders rejected incur a lost sales cost. The objective is to minimize
European Journal of Operational Research, 2010
Computers & Industrial Engineering, 1997
This paper considers the scheduling of a manufacturing system with nonresumable setup changes. Th... more This paper considers the scheduling of a manufacturing system with nonresumable setup changes. The system considered involves an unreliable machine that can produce two part types. The switchover from one part type to the other incurs a given constant setup time. The setups are nonresumable, i.e. after a machine repair completion, a setup decision has to be made. The parts have specified constant processing time and constant demand rate. We give a continuous dynamic programming formulation of the problem, which is solved numerically. The optimal setup switching policies are shown to be hedging corridors. Two heuristics, for the determination of the hedging levels, are provided. We show, through simulation, that the two heuristics exhibit good performance.
We consider the optimal control of an assemble-to-order (ATO) system with m components, a single ... more We consider the optimal control of an assemble-to-order (ATO) system with m components, a single end-product, and n customer classes. Demand from each class occurs continuously over time according to a Poisson process. Components are produced in separate production facilities, each with a finite production rate and exponentially distributed production times. Components can be stocked ahead of demand but incur
We consider an assembly system with multiple stages, multiple items, and multiple customer classe... more We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced in variable batch sizes, one batch at a time, with exponentially distributed batch production times. Demand from each class takes place continuously over time according to a compound Poisson process. At
We consider an assembly system with multiple stages, multiple items, and multiple customer classe... more We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced one unit at a time. To produce one unit of an item, one unit from each of its predecessor items is needed. Upon production completion, items are placed in inventory. At
OR Spektrum, 1996
In this paper, we study a manufacturing system consisting of two machines separated by two interm... more In this paper, we study a manufacturing system consisting of two machines separated by two intermediate buffers, and capable of producing two different products. Each product requires a constant processing time on each of the machines. Each machine requires a constant non-negligible setup change time from one product to the other. The demand rate for each product is considered to be piecewise constant. Each machine undergoes failure and repair. The time-to-failure and time-to-repair are exponentially distributed random variables. The setup change and processing operations are resumable. We model our system as a continuous time, continuous flow process. An optimal control problem is formulated for the system to minimize the total expected discounted cost over an infinite horizon. To determine the optimal control policy structure, a discrete version of the problem is solved numerically using a dynamic programming formulation with a piecewise linear penalty function. A real-time control algorithm is then developed with the objective of maintaining low work-in-process inventory and keeping the production close to the demand. The algorithm uses a hierarchical control structure to generate the loading times for each product on each machine in real time and to respond to random disruptions in the system. The system is simulated using this algorithm to study its performance. The performance of the algorithm is also compared to alternative policies.
Proceedings of the Fourth International Conference on Computer Integrated Manufacturing and Automation Technology, 1994
In this paper, we study the scheduling of a deterministic one-machine two-part-type setup system ... more In this paper, we study the scheduling of a deterministic one-machine two-part-type setup system under steady and transient conditions. The optimal solution, expressed as an optimal feedback control, provides the optimal production rates and setup switching epochs as a function of the state of the system. For the steady state, the optimal cyclic schedule is determined. For the transient case,
International Journal of Production Research, 2014
ABSTRACT This paper studies a single end product assemble-to-order system serving both the demand... more ABSTRACT This paper studies a single end product assemble-to-order system serving both the demand of the end product and the individual components. Demands are assumed to form independent Poisson streams with different rates. Unsatisfied demand, both for the end product and for components, is assumed lost and thus incurs a per unit lost sale penalty. The end product is assembled from K distinct components each produced on a different production facility (or procured from independent suppliers). Production lead times are non-identical and are assumed to be independent and exponentially distributed. Produced components are held in stock in anticipation of future demands. The goal is to determine the optimal component production and inventory allocation policy. The optimal policy is characterised using a Markov Decision Process model. It is shown that, in addition to the state-dependent threshold type, the optimal policy exhibits counter-intuitive features which have not been observed in systems without components demand. In particular, for certain combinations of system parameters, the optimal inventory allocation policy switches priority as the inventory level of components changes. Furthermore, for a particular component k, as the inventory level of other components increases, the desirability of satisfying Component k demand decreases. Finally, because in general the optimal policy is fairly complicated and is difficult to obtain numerically, due to the curse of dimensionality of dynamic programming, three heuristic policies are proposed. Extensive numerical experiments indicate that the three heuristics perform very well compared to the optimal policy.
Journal of Global Optimization, 1996
This paper deals with the optimal scheduling of a one-machine two-product manufacturing system wi... more This paper deals with the optimal scheduling of a one-machine two-product manufacturing system with setup, operating in a continuous time dynamic environment. The machine is reliable. A known constant setup time is incurred when switching over from a part to the other. Each part has specified constant processing time and constant demand rate, as well as an infinite supply of
Management Science, 2004
We consider the problem of allocating demand arising from N products to M production facilities w... more We consider the problem of allocating demand arising from N products to M production facilities with finite capacity and load-dependent manufacturing lead-times. Production facilities can choose to manufacture items either to-stock or to-order. If items are stocked, demand is satisfied immediately if there is on-hand inventory. Otherwise, demand is backlogged with the production facility to which it is assigned. Products
Production and Operations Management, 2009
Operations Research, 2011
Journal of Global Optimization, 1997
In this paper, we deal with the production scheduling ofseveral products that are produced period... more In this paper, we deal with the production scheduling ofseveral products that are produced periodically, in a fixed sequence, ona single machine. In the literature, this problem is usually referred to asthe Common Cycle Economic Lot Scheduling Problem. We extend thelatter to allow the production rates to be controllable at the beginningof as well as during each production run of a product. Also, we assumethat unsatisfied demand is completely backordered. The objective is todetermine the optimal schedule that satisfies the demand for all theproducts and that realizes the minimum average setup, inventoryholding and backlog cost per unit time. Comparison with previousresults (when production rates are fixed) reveals that averagecosts can be reduced up to 66% by allowing controllable productionrates.
Journal of Global Optimization, 1996
This paper deals with the optimal control of a one-machine two-product manufacturing system with ... more This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as
International Journal of Production Research, 2008
IEEE Transactions on Automation Science and Engineering, 2000
We consider a production-inventory system with two customer classes, one patient and one impatien... more We consider a production-inventory system with two customer classes, one patient and one impatient. Orders from the patient class can be backordered if needed, while orders from the impatient class must be rejected if they cannot be fulfilled from on-hand inventory. Orders backordered incur a backorder cost, while orders rejected incur a lost sales cost. The objective is to minimize
European Journal of Operational Research, 2010
Computers & Industrial Engineering, 1997
This paper considers the scheduling of a manufacturing system with nonresumable setup changes. Th... more This paper considers the scheduling of a manufacturing system with nonresumable setup changes. The system considered involves an unreliable machine that can produce two part types. The switchover from one part type to the other incurs a given constant setup time. The setups are nonresumable, i.e. after a machine repair completion, a setup decision has to be made. The parts have specified constant processing time and constant demand rate. We give a continuous dynamic programming formulation of the problem, which is solved numerically. The optimal setup switching policies are shown to be hedging corridors. Two heuristics, for the determination of the hedging levels, are provided. We show, through simulation, that the two heuristics exhibit good performance.