Today’s competitive markets force companies to produce high-quality, customized products at low cost under substantial time pressure. Companies do various things to speed up their operations and meet such promised lead-times. Researchers developed optimization models that jointly capture decisions on locations, production strategies and transport operations for a supply chain. The optimization models capture the interdependencies of the various lead-time drivers, and they help quantify the trade-off of lead-times and cost in a supply chain. They conduct computational experiments to identify those design decisions that have the highest impact on the lead-time and the cost of a supply chain. They found that location decisions together with a well-chosen separation of a supply chain into a downstream make-to-stock part and an upstream make-to-order part are of utmost importance. Transportation decisions seem to have a minor impact. The presented approach is sufficiently general to be applied to various types of products and industries.
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