We consider an assemble-to-order M-system with multiple components, multiple products, batch ordering of components, random lead times, and lost sales. We model the system as an infinite-horizon Markov decision process and seek an optimal control policy: a control policy specifies when a batch of components should be produced, and whether an arriving demand for each product should be satisfied.We introduce new functional characterizations for submodularity and supermodularity restricted to certain subspaces. These enable us to characterize optimal inventory replenishment and allocation policies under a mild condition on component batch sizes via a new type of policy: lattice-dependent base-stock production and lattice-dependent rationing.</...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
This thesis examines two complex, dynamic problems by employing the theory of Markov De-cision Proce...
Cataloged from PDF version of article.We consider an assemble-to-order generalized M-system with mul...
We consider an assemble-to-order generalized M-system with multiple components and multiple products...
We consider an assemble-to-order (ATO) system with multiple products, multiple components which may ...
We consider an assemble-to-order system with multiple products, multiple components which may be dem...
Abstract: We consider the optimal control of an assemble-to-order (ATO) system with m components, a ...
We consider an assemble-to-order system with a high volume of prospective customers arriving per uni...
This thesis examines two complex, dynamic problems by employing the theory of Markov Decision Proces...
<p>This thesis examines two complex, dynamic problems by employing the theory of Markov</p> <p>Decis...
We consider the optimal production and inventory control of an assemble-to-order system with m compo...
We analyze a W-configuration assemble-to-order system with random lead times, random arrival of dema...
We consider an assemble-to-order (ATO) system with multiple products, multiple components which may ...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
This thesis examines two complex, dynamic problems by employing the theory of Markov De-cision Proce...
Cataloged from PDF version of article.We consider an assemble-to-order generalized M-system with mul...
We consider an assemble-to-order generalized M-system with multiple components and multiple products...
We consider an assemble-to-order (ATO) system with multiple products, multiple components which may ...
We consider an assemble-to-order system with multiple products, multiple components which may be dem...
Abstract: We consider the optimal control of an assemble-to-order (ATO) system with m components, a ...
We consider an assemble-to-order system with a high volume of prospective customers arriving per uni...
This thesis examines two complex, dynamic problems by employing the theory of Markov Decision Proces...
<p>This thesis examines two complex, dynamic problems by employing the theory of Markov</p> <p>Decis...
We consider the optimal production and inventory control of an assemble-to-order system with m compo...
We analyze a W-configuration assemble-to-order system with random lead times, random arrival of dema...
We consider an assemble-to-order (ATO) system with multiple products, multiple components which may ...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
We provide a new method for solving a very general model of an assemble-toorder system: multiple pro...
This thesis examines two complex, dynamic problems by employing the theory of Markov De-cision Proce...