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dc.contributor.authorAraya-Sassi, Claudio
dc.contributor.authorMiranda, Pablo A.
dc.contributor.authorParedes-Belmar, Germán
dc.description.abstractWe studied a joint inventory location problem assuming a periodic review for inventory control. A single plant supplies a set of products tomultiple warehouses and they serve a set of customers or retailers.The problem consists in determining which potential warehouses should be opened and which retailers should be served by the selected warehouses as well as their reorder points and order sizes while minimizing the total costs. The problem is a Mixed Integer Nonlinear Programming (MINLP) model, which is nonconvex in terms of stochastic capacity constraints and the objective function. We propose a solution approach based on a Lagrangian relaxation and the subgradient method. The decomposition approach considers the relaxation of different sets of constraints, including customer assignment, warehouse demand, and variance constraints. In addition, we develop a Lagrangian heuristic to determine a feasible solution at each iteration of the subgradientmethod.The proposed Lagrangian relaxation algorithm provides low duality gaps and near-optimal solutions with competitive computational times. It also shows significant impacts of the selected inventory control policy into total system costs and network configuration, when it is compared with different review period values.es_ES
dc.sourceMathematical Problems in Engineering
dc.subjectLagrangian relaxationes_ES
dc.subjectSubgradient methodes_ES
dc.subjectSupply chaines_ES
dc.subjectSupply chain network designes_ES
dc.titleLagrangian Relaxation for an Inventory Location Problem with Periodic Inventory Control and Stochastic Capacity Constraintses_ES
dc.typeArtículo de revistaes_ES
uvm.escuelaEscuela de Ingeniería y Negocioses_ES

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