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Communication Dans Un Congrès Année : 2023

A Scenario Generation Method Exploring Uncertainty and Decision Spaces for Robust Strategic Supply Chain Capacity Planning

Raphaël Oger
Cléa Martinez

Résumé

Strategic Supply Chain Capacity Planning (SSCCP) is an essential activity for companies to prepare their future. However, since uncertainty became an essential factor to consider in this decision-making process, existing solutions to support this process do not fully satisfy their needs anymore. Especially in terms of uncertainty space coverage while exploring and assessing scenarios associated with uncertainty sources and decision options. Therefore, this paper introduces an approach to overcome the complexity of scenario exploration and improve the uncertainty space coverage, to better support SSCCP decision-making. This approach includes a bi-objective metaheuristic that first explores a probability-impact matrix to define a relevant subspace to consider in this uncertainty space, and then uses this subspace to explore the decision space and define a relevant subspace of this decision space to assess and display to decision-makers. Then, an implementation and experiment are described and discussed, and finally avenues for future research are suggested. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Achille Poirier, Raphaël Oger, Cléa Martinez. A Scenario Generation Method Exploring Uncertainty and Decision Spaces for Robust Strategic Supply Chain Capacity Planning. IN4PL 2023 - 4th International Conference on Innovative Intelligent Industrial Production and Logistics, Nov 2023, Rome, Italy. pp.126-148, ⟨10.1007/978-3-031-49339-3_8⟩. ⟨hal-04428323⟩
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