An extended graph-based virtual clustering-enhanced approach to supply chain optimisation

This paper describes the work that led to the realisation of an extended graph-based virtual clustering-enhanced approach to supply chain optimisation. The Supply-Chain Operations Reference (SCOR) model defined by the Supply-Chain Council in Pittsburgh, PA, USA is used to denote a typical supply chain, which may include geographically distributed suppliers, warehouses, factories, distribution centres (DCs), transportation and customers. A graph representation is proposed to represent and analyse the business processes of the SCOR model from customer orders to suppliers. Furthermore, logical relationships are superimposed onto the graph. This extended graph enables the complex relationships between the nodes of two adjoining layers to be described. By so doing, it is able to model a complex supply chain with multiple level assembly, various types of transportations and a multiple split and merge of orders. In order to handle a large-scale supply chain optimisation problem, the extended graph is enhanced by virtual clustering so as to realise an approach that is able to downscale the optimisation problem and reduce the search space. A case study is used to illustrate the effectiveness of the proposed approach. The details of the SCOR model, the extended graph, the virtual clustering, the proposed approach and the case study are presented in this paper.

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