Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging
Open Access
- 7 June 2021
- journal article
- meeting abstracts
- Published by Association for Computing Machinery (ACM) in ACM SIGMETRICS Performance Evaluation Review
- Vol. 49 (1), 67-68
- https://doi.org/10.1145/3543516.3456271
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 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, in the full version of this paper, we illustrate the proposed algorithm via trace-based experiments of EV charging.Keywords
Funding Information
- NSF (CNS-1908298, CAREER 2045641, CPS ECCS 1932611, CPS ECCS 1739355, AitF-1637598, CNS-1518941)
- Hong Kong Research Grant Council (RGC) General Research Fund (Project 16202619, Project 16211220)
This publication has 2 references indexed in Scilit:
- Budget Constrained Bidding in Keyword Auctions and Online Knapsack ProblemsLecture Notes in Computer Science, 2008
- Optimal Search and One-Way Trading Online AlgorithmsAlgorithmica, 2001