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Neural Inventory Control in Networks via Hindsight Differentiable Policy Optimization
Second, we propose a natural neural network architecture to address problems with weak (or aggregate) coupling constraints between locations in an inventory network.
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We introduce a benchmark model with heterogeneous "workers" (demand) and a limited supply of "jobs" that arrive over time.
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