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We consider a maintenance service provider that services geographically dispersed customers with its local service engineers. Traditionally, when a system failure is reported, a service engineer makes a diagnostic visit to the customer's location to perform corrective maintenance
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Thanks to Industry 4.0 technologies, predictive algorithms can provide advance demand information on spare parts demand. Understanding how the goodness of predictions affects on-hand inventory and costs is important for decision makers before integrating these models into existin
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A popular method in machine learning for super-vised classification is a decision tree. In this work we propose a new framework to learn fuzzy decision trees using mathematical programming. More specifically, we encode the problem of constructing fuzzy decision trees using a Mixe
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In this work, we propose a re-enactment simulation-based optimization method to determine the minimal total buffer capacity in an assembly line required to meet a target throughput. A distinguishing feature is the use of real-time event traces, in a fast fluid flow simulation mod
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