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Online Line Aggregation with Deadlines: Randomized Guarantees and Learning-Augmented Tradeoffs
We study online line aggregation with deadlines, where requests arrive over time on the positive half-line and a service at location $y$ clears all pending requests in $[0,y]$ at cost $y$. In the classical adversarial setting, we propose an $e$-competitive randomized algorithm against an oblivious a
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