Flexibility evaluation of multiechelon supply chains

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain...

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Bibliographic Details
Published in:PloS one 2018-03, Vol.13 (3), p.e0194050-e0194050
Main Authors: Almeida, João Flávio de Freitas, Conceição, Samuel Vieira, Pinto, Luiz Ricardo, de Camargo, Ricardo Saraiva, Júnior, Gilberto de Miranda
Format: Article
Language:English
Subjects:
Demand analysis
Engineering and Technology
Flexibility
Logistics
Management
Manufacturing
Mathematical models
Mathematical programming
Parameters
Physical Sciences
Procurement
Research and Analysis Methods
Robustness (mathematics)
Social responsibility
Social Sciences
Stochasticity
Suppliers
Supply chains
Uncertainty
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Summary:Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0194050