Details

Autor(en) / Beteiligte

• Sun, Bo
• Zeynali, Ali
• Li, Tongxin
• Hajiesmaili, Mohammad
• Wierman, Adam
• Tsang, Danny H.K.

Titel

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

Ist Teil von

• Proceedings of the ACM on measurement and analysis of computing systems, 2020-11, Vol.4 (3), p.1-32, Article 51

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2020

Quelle

ACM Digital Library

Beschreibungen/Notizen

• 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.