Abstract
A geographical concentration of nodes within a supply chain or supply chain density is one of the supply chain network characteristics that may affect the resiliency of a supply chain to disruption. Some major cases include the disruption of the global PC supply chain due to the 1999 earthquake in Taiwan, the disruption of automotive supply chain due to the 2011 earthquake in Japan, and the disruption of hard disk supply chain due to the 2011 massive floods in Thailand. These disruptions were resulted from the high geographical concentration of suppliers and manufacturers. In this chapter, the optimal design of a supply chain is discussed with the objectives of maximizing the total profit and the density of the supply chain. A bi-criteria mixed-integer linear programming model (MILP) is formulated to determine the optimal locations of the facilities and the distribution of flows between facilities in the supply chain. A four-stage supply chain network model is developed, which consists of suppliers, manufacturing plants, warehouses, and retailers. The model is illustrated using a realistic example, and the results are discussed.
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Rienkhemaniyom, K., Pazhani, S. (2015). A Supply Chain Network Design Considering Network Density. In: Kachitvichyanukul, V., Sethanan, K., Golinska- Dawson, P. (eds) Toward Sustainable Operations of Supply Chain and Logistics Systems. EcoProduction. Springer, Cham. https://doi.org/10.1007/978-3-319-19006-8_1
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DOI: https://doi.org/10.1007/978-3-319-19006-8_1
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