Capacity-Insensitive Algorithms for Online Facility Assignment Problems on a Line
Tsubasa Harada, Toshiya Itoh, Shuichi Miyazaki

TL;DR
This paper introduces capacity-insensitive algorithms for online facility assignment on a line, establishing bounds on their competitive ratios and proposing an optimal MPFS algorithm called IDAS.
Contribution
The paper proves capacity-insensitivity of MPFS algorithms, derives bounds for greedy algorithms, and introduces IDAS, an optimal MPFS algorithm for the problem.
Findings
Greedy algorithm GRDY has a competitive ratio of 4k-5 on equidistant servers.
Any MPFS algorithm has a competitive ratio of at least 2k-1.
IDAS achieves a competitive ratio of at most 2k-1, matching the lower bound.
Abstract
In the online facility assignment problem OFA(k,\ell), there exist k servers with a capacity \ell \geq 1 on a metric space and a request arrives one-by-one. The task of an online algorithm is to irrevocably match a current request with one of the servers with vacancies before the next request arrives. As special cases for OFA(k,\ell), we consider OFA(k,\ell) on a line, which is denoted by OFAL(k,\ell) and OFAL_{eq}(k,\ell), where the latter is the case of OFAL(k,\ell) with equidistant servers. In this paper, we deal with the competitive analysis for the above problems. As a natural generalization of the greedy algorithm GRDY, we introduce a class of algorithms called MPFS (most preferred free servers) and show that any MPFS algorithm has the capacity-insensitive property, i.e., for any \ell \geq 1, ALG is c-competitive for OFA(k,1) iff ALG is c-competitive for OFA(k,\ell). By applying…
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Taxonomy
TopicsOptimization and Search Problems · Facility Location and Emergency Management · Auction Theory and Applications
