A 5-Approximation for Universal Facility Location

Authors Manisha Bansal, Naveen Garg, Neelima Gupta

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Manisha Bansal
  • Indraprastha College for Women, University of Delhi, India
Naveen Garg
  • Indian Institute of Technology Delhi, India
Neelima Gupta
  • University of Delhi, India

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Manisha Bansal, Naveen Garg, and Neelima Gupta. A 5-Approximation for Universal Facility Location. In 38th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 122, pp. 24:1-24:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


In this paper, we propose and analyze a local search algorithm for the Universal facility location problem. Our algorithm improves the approximation ratio of this problem from 5.83, given by Angel et al., to 5. A second major contribution of the paper is that it gets rid of the expensive multi operation that was a mainstay of all previous local search algorithms for capacitated facility location and universal facility location problem. The only operations that we require to prove the 5-approximation are add, open, and close. A multi operation is basically a combination of the open and close operations. The 5-approximation algorithm for the capacitated facility location problem, given by Bansal et al., also uses the multi operation. However, on careful observation, it turned out that add, open, and close operations are sufficient to prove a 5-factor for the problem. This resulted into an improved algorithm for the universal facility location problem, with an improved factor.

Subject Classification

ACM Subject Classification
  • General and reference → Reference works
  • General and reference → General conference proceedings
  • Theory of computation → Facility location and clustering
  • Facility location
  • Approximation Algorithms
  • Local Search


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