Online Task Assignment Problems with Reusable Resources
Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro, Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi

TL;DR
This paper introduces an online task assignment model with reusable agents and multiple task accommodations, proposing a $1/2$-competitive algorithm and analyzing its performance under rejection constraints, supported by numerical experiments.
Contribution
We develop a novel online algorithm for reusable resource task assignment with proven competitive ratios and extend analysis to rejection constraints, addressing practical applications.
Findings
The algorithm achieves a $1/2$-competitive ratio, which is proven to be tight.
Under rejection constraints, the competitive ratio is at least 1/3.
Numerical experiments validate the effectiveness of the proposed algorithm.
Abstract
We study online task assignment problem with reusable resources, motivated by practical applications such as ridesharing, crowdsourcing and job hiring. In the problem, we are given a set of offline vertices (agents), and, at each time, an online vertex (task) arrives randomly according to a known time-dependent distribution. Upon arrival, we assign the task to agents immediately and irrevocably. The goal of the problem is to maximize the expected total profit produced by completed tasks. The key features of our problem are (1) an agent is reusable, i.e., an agent comes back to the market after completing the assigned task, (2) an agent may reject the assigned task to stay the market, and (3) a task may accommodate multiple agents. The setting generalizes that of existing work in which an online task is assigned to one agent under (1). In this paper, we propose an online algorithm that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
Taxonomy
TopicsOptimization and Search Problems · Transportation and Mobility Innovations · Auction Theory and Applications
