Nadar, E.Akan, M.Scheller-Wolf, A.2016-02-082016-02-0820140030-364Xhttp://hdl.handle.net/11693/26505We consider an assemble-to-order generalized M-system with multiple components and 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 policy that specifies when a batch of components should be produced (i.e., inventory replenishment) and whether an arriving demand for each product should be satisfied (i.e., inventory allocation). We 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 and lattice-dependent rationing. © 2014 INFORMS.EnglishAssemble-to-order systemsLattice-dependent policiesMarkov decision processesOptimal controlFlash memoryLearning algorithmsMarkov processesAllocation policiesAssemble-to-orderInfinite horizonsInventory allocationInventory replenishmentMarkov Decision ProcessesMultiple componentsOptimal controlsStructural optimizationArticle10.1287/opre.2014.12711526-5463