The Online Knapsack Problem with Departures

The online knapsack problem is a classic resource allocation in networking and operations research. Its basic version studies how to pack arriving items of different sizes values into capacity-limited knapsack. In this paper, we study general that includes item departures, while also considering multiple knapsacks multi-dimensional sizes. We design threshold-based algorithm prove the can achieve order-optimal competitive ratios. Beyond worst-case performance guarantees, aim near-optimal average under typical instances. Towards goal, propose data-driven learns within policy-class guarantees bound. trace-driven experiments, show our outperforms other benchmark algorithms an application job scheduling for cloud computing.