Online Multi-Facility Location
Christine Markarian, Abdul-Nasser Kassar, Manal Yunis

TL;DR
This paper introduces the first online algorithms for Multi-Facility Location problems, addressing scenarios where clients require multiple facilities, and evaluates their performance through competitive analysis in worst-case settings.
Contribution
It presents novel online algorithms for both metric and non-metric Multi-Facility Location problems, expanding the scope of facility location research.
Findings
First online algorithms for Multi-Facility Location problems.
Performance measured via competitive analysis in worst-case scenarios.
Addresses both metric and non-metric variants.
Abstract
Facility Location problems ask to place facilities in a way that optimizes a given objective function so as to provide a service to all clients. These are one of the most well-studied optimization problems spanning many research areas such as operations research, computer science, and management science. Traditionally, these problems are solved with the assumption that clients need to be served by one facility each. In many real-world scenarios, it is very likely that clients need a robust service that requires more than one facility for each client. In this paper, we capture this robustness by exploring a generalization of Facility Location problems, called Multi-Facility Location problems, in the online setting. An additional parameter k, which represents the number of facilities required to serve a client, is given. We propose the first online algorithms for the metric and non-metric…
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Taxonomy
TopicsOptimization and Search Problems · Facility Location and Emergency Management · Complexity and Algorithms in Graphs
