Supply chain operations and scheduling are well-studied problems in the literature. Although these problems are related, they are often solved sequentially. This uncoordinated approach usually leads to suboptimal solutions. This paper proposes a methodology for integrating scheduling operations into the supply chain network, motivated by the available enterprise data, and feasibility analysis. Existing literature on integrated models for addressing the supply chain is reviewed and classified. Then the mathematical model formulation for each level is discussed, after which the proposed data-driven integrated framework is described. The methodology is tested on two different case studies of varying dimensions. For each case study, the solution solves a multi-objective problem with the overall aim of an optimal solution that is robust towards achieving optimal cost while keeping customer satisfaction in mind. (c) 2022 Elsevier Ltd. All rights reserved.
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Leiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, NetherlandsLeiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, Netherlands
Schuurman, Bart
Bakker, Edwin
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Leiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, NetherlandsLeiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, Netherlands
Bakker, Edwin
Gill, Paul
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UCL, Dept Secur & Crime Sci, 35 Tavistock Sq, London WC1H 9EZ, EnglandLeiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, Netherlands
Gill, Paul
Bouhana, Noemie
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UCL, Dept Secur & Crime Sci, 35 Tavistock Sq, London WC1H 9EZ, EnglandLeiden Univ, Inst Secur & Global Affairs, Turfmarkt 99, NL-2511 DV The Hague, Netherlands
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TU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, AustriaTU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, Austria
Fenz, Stefan
Neubauer, Thomas
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TU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, AustriaTU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, Austria
Neubauer, Thomas
Friedel, Juergen Kurt
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Univ Nat Resources & Life Sci, Div Organ Farming, Gregor Mendel Str 33, A-1180 Vienna, AustriaTU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, Austria
Friedel, Juergen Kurt
Wohlmuth, Marie-Luise
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Univ Nat Resources & Life Sci, Div Organ Farming, Gregor Mendel Str 33, A-1180 Vienna, AustriaTU Wien, Inst Informat Syst Engn Data Sci, Favoritenstr 9-11, A-1040 Vienna, Austria