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This invention describes a computer system designed to figure out the best places to put resources within a service network to ensure customer demand is met, even when parts of the network fail. It works by creating a detailed, time-based map of the network, considering various potential failure events and their likelihoods, and then calculates the optimal resource arrangement to minimize service disruptions. The claims specifically detail this process using a 'multi-commodity flow network graph' model.
Why it matters: Filed before significant advancements in AI and machine learning made complex optimization problems, especially those involving probabilistic scenarios and large networks, more tractable and efficient to solve. Cloud computing also makes deploying such systems more scalable.
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