Designing an efficient supply chain network with uncertain data: a robust optimization–data envelopment analysis approach

Designing an efficient supply chain network with uncertain data: a robust optimization–data envelopment analysis approach

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Article ID: iaor20172624
Volume: 68
Issue: 7
Start Page Number: 816
End Page Number: 828
Publication Date: Jul 2017
Journal: J Oper Res Soc
Authors: , ,
Keywords: combinatorial optimization, design, networks, statistics: data envelopment analysis, decision, simulation
Abstract:

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.

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