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Strategic supply chain design decisions are critical to the long-term success of a business. Traditional facility location models for supply chain design focus on the trade-offs between the costs and benefits of proximity, i.e., the distance between facilities and customers. These strategic-focused models do not consider the supply chain's agility, i.e., its ability to quickly respond to unexpected fluctuations in customer needs. In this paper, we study the problem of designing a supply chain distribution network under demand uncertainty and analyze how the optimal design characteristics of proximity and agility depend on various input parameters. We are able to draw managerial insights on how agility considerations may invalidate well-established and widely accepted qualitative results derived from traditional models. In particular, we show that it is optimal to increase the density of distribution centers (DCs) when the shortage penalty cost increases, and to decrease the density of DCs when a certain unit transportation cost parameter increases. Through these findings, our work conveys the message that traditional, proximity-based facility location models can be inadequate for designing modern responsive supply chains, and calls for the need to develop a new class of models for the task. This paper was accepted by Yossi Aviv, operations management. [ABSTRACT FROM AUTHOR]

Recent research has pointed out that the optimal strategies to mitigate supply disruptions and demand uncertainty are often mirror images of each other. In particular, risk diversification is favorable under the threat of disruptions and risk pooling is favorable under demand uncertainty. This article studies how dynamic sourcing in supply chain design provides partial benefits of both strategies. Optimization models are formulated for supply chain network design with dynamic sourcing under the risk of temporally dependent and temporally independent disruptions of facilities. Using computational experiments, it is shown that supply chain networks that allow small to moderate degrees of dynamic sourcing can be very robust against both disruptions and demand uncertainty. Insights are attained on the optimal degree of dynamic sourcing under different conditions. [ABSTRACT FROM PUBLISHER]

The article presents a study on the optimization of the location of two-echelon spare parts inventory system along with service considerations. A mixed integer nonlinear programming model (MINLP) was formulated to be used in designing service parts network that will ensure short response times. It reveals that using a response time requirement is less costly in the achievement of a target response time than through penalty costs.