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An Approximate Method for Integrated Stochastic Replenishment Planning with Supplier Selection

Rabin Sahu 1 Clarisse Dhaenens 2 Nadarajen Veerapen 1 Manuel Davy 3
1 ORKAD - Operational Research, Knowledge And Data
CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
3 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal, Inria Lille - Nord Europe
Abstract : A practical methodology for integrated stochastic replenishment planning with supplier selection is proposed for the single item inventory system. A rolling horizon strategy is adopted to implement the ordering decisions. Our method works in two stages. The first stage is a general black box stage that gives the minimum expected "coverage period" cost. The second stage uses a dynamic programming approach to compute the minimum expected cost for the rolling horizon. The proposed method is applicable for both stationary and non-stationary demand distributions and even for problems with minimum order quantity constraints. We also propose to examine the benefits of a dynamic supplier selection approach in comparison to selecting a common supplier. We conduct extensive numerical analyses on synthetic data sets for validation.
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Submitted on : Thursday, March 12, 2020 - 10:38:46 AM
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Rabin Sahu, Clarisse Dhaenens, Nadarajen Veerapen, Manuel Davy. An Approximate Method for Integrated Stochastic Replenishment Planning with Supplier Selection. International Conference on Operations Research and Enterprise Systems - ICORES 2020, Feb 2020, Valletta, Malta. ⟨hal-02503109⟩

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