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arXiv · 2010.00412

Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging

Bo Sun·Ali Zeynali·Tongxin Li·Mohammad Hajiesmaili·Adam Wierman·Danny H. K. Tsang
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Abstract

We introduce and study a general version of the fractional online knapsack problem with multiple knapsacks, heterogeneous constraints on which items can be assigned to which knapsack, and rate-limiting constraints on the assignment of items to knapsacks. This problem generalizes variations of the knapsack problem and of the one-way trading problem that have previously been treated separately, and additionally finds application to the real-time control of electric vehicle (EV) charging. We introduce a new algorithm that achieves a competitive ratio within an additive factor of one of the best achievable competitive ratios for the general problem and matches or improves upon the best-known competitive ratio for special cases in the knapsack and one-way trading literatures. Moreover, our analysis provides a novel approach to online algorithm design based on an instance-dependent primal-dual analysis that connects the identification of worst-case instances to the design of algorithms. Finally, we illustrate the proposed algorithm via trace-based experiments of EV charging.

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Bo Sun, Ali Zeynali, Tongxin Li, Mohammad Hajiesmaili, Adam Wierman, Danny H. K. Tsang. 2020-10-17. Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. https://arxiv.org/abs/2010.00412

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