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Designing an efficient supply chain network with uncertain data: a robust optimization-data envelopment analysis approach
Ist Teil von
The Journal of the Operational Research Society, 2017-07, Vol.68 (7), p.816-828
Ort / Verlag
London: Taylor & Francis
Erscheinungsjahr
2017
Link zum Volltext
Quelle
Taylor & Francis Journals Auto-Holdings Collection
Beschreibungen/Notizen
Designing a supply chain network (SCN) is an important issue for organizations in competitive markets. In this paper, a novel robust SCN that considers the efficiencies and costs simultaneously is proposed. In order to estimate the efficiency of the producers and distributors, data envelopment analysis (DEA) model is incorporated into SCN. Moreover, to handle the uncertainty in data, a scenario-based robust optimization approach is applied. The proposed model finds out the efficient location of producers and distributors and determines the amount of purchases from each supplier in uncertain conditions. To illustrate the application of the proposed model, a numerical example is solved and results are analyzed.