A Caltech Library Service

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

Sun, Bo and Zeynali, Ali and Li, Tongxin and Hajiesmaili, Mohammad and Wierman, Adam and Tsang, Danny H. K. (2020) Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. . (Unpublished)

[img] PDF - Submitted Version
See Usage Policy.


Use this Persistent URL to link to this item:


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.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Li, Tongxin0000-0002-9806-8964
Hajiesmaili, Mohammad0000-0001-9278-2254
Tsang, Danny H. K.0000-0003-0135-7098
Record Number:CaltechAUTHORS:20201014-142839691
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106066
Deposited By: Tony Diaz
Deposited On:14 Oct 2020 21:49
Last Modified:14 Oct 2020 21:49

Repository Staff Only: item control page