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Title: Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging
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.  more » « less
Award ID(s):
1908298 1637598
PAR ID:
10296409
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Volume:
4
Issue:
3
ISSN:
2476-1249
Page Range / eLocation ID:
1 to 32
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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