Digital Equipment Corporation evaluates global supply chain alternatives and determines worldwide manufacturing and distribution strategy, using the Global Supply Chain Model (GSCM) which recommends a production, distribution, and vendor network. GSCM minimizes cost or weighted cumulative production and distribution times or both subject to meeting estimated demand and restrictions on local content, offset trade, and joint capacity for multiple products, echelons, and time periods. Cost factors include fixed and variable production charges, inventory charges, distribution expenses via multiple modes, taxes, duties, and duty drawback. GSCM is a large mixed-integer linear program that incorporates a global, multi-product bill of materials for supply chains with arbitrary echelon structure and a comprehensive model of integrated global manufacturing and distribution decisions. The supply chain restructuring has saved over $100 million (US).

We use a simulation model called ‘SISCO’ to examine the effects in supply chains of stochastic lead times and of information sharing and quality of that information in a periodic order‐up‐to level inventory system. We test the accuracy of the simulation by verifying the results in Chen et al. (2000a) and Dejonckheere et al. (2004). We find that lead‐time variability exacerbates variance amplification in a supply chain, and that information sharing and information quality are highly significant. For example, using the assumptions in Chen et al. (2000a) and Dejonckheere et al. (2004), we find in a numerical experiment of a customer‐retailer‐wholesaler‐distributor‐factory supply chain that variance amplification is attenuated by nearly 50 percent at the factory due to information sharing. Other assumptions we make are based on interviews or conversations with managers at large supply chains.

Closed-loop supply chains differ significantly from forward supply chains in many aspects. These differences are not well understood in many contexts, and the situation is complicated by many types of product returns. Progress is slow since closed-loop supply chains are rarely considered as value-creating systems, and much of the focus is on the operational aspects, rather than the larger strategic issues. Interest is growing in the US because of the potential profitability and in the European Union because of legislation. New business models need to be developed by joint cooperation between industry and academia that take a life-cycle approach to products. (Facilities, equipment planning: capacity expansion. Manufacturing: performance, productivity.)

Abstract-In this paper, we study the resilience of supply networks against disruptions and provide insights to supply chain managers on how to construct a resilient supply network from the perspective of complex network topologies. Our goal is to study how different network topologies, which are created from different growth models, affect the network's resilience against both random and targeted disruptions. Of particular interest are situations where the type of disruption is unknown. Using a military logistic network as a case study, we propose new network resilience metrics that reflect the heterogeneous roles (e.g., supply, relay, and demand) of nodes in supply networks. We also present a hybrid and tunable network growth model called Degree and Locality-based Attachment (DLA), in which new nodes make connections based on both degree and locality. Using computer simulations, we compare the resilience of several supply network topologies that are generated with different growth models. The results show that the new resilience metrics can capture important resilience requirements for supply networks very well. We also found that the supply network topology generated by the DLA model provides balanced resilience against both random and targeted disruptions.

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