EconPapers    
Economics at your fingertips  
 

An efficient algorithm for the single facility location problem with polyhedral norms and disk-shaped demand regions

André Berger (), Alexander Grigoriev and Andrej Winokurow ()

Computational Optimization and Applications, 2017, vol. 68, issue 3, No 9, 669 pages

Abstract: Abstract The single facility location problem with demand regions seeks for a facility location minimizing the sum of the distances from n demand regions to the facility. The demand regions represent sales markets where the transportation costs are negligible. In this paper, we assume that all demand regions are disks of the same radius, and the distances are measured by a rectilinear norm, e.g. $$\ell _1$$ ℓ 1 or $$\ell _\infty $$ ℓ ∞ . We develop an exact combinatorial algorithm running in time $$O(n\log ^c n)$$ O ( n log c n ) for some c dependent only on the space dimension. The algorithm is generalizable to the other polyhedral norms.

Keywords: 1-median; Single facility location problem; Rectilinear norm; Polyhedral norm; Exact algorithm (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10589-017-9935-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:coopap:v:68:y:2017:i:3:d:10.1007_s10589-017-9935-4

Ordering information: This journal article can be ordered from
http://www.springer.com/math/journal/10589

DOI: 10.1007/s10589-017-9935-4

Access Statistics for this article

Computational Optimization and Applications is currently edited by William W. Hager

More articles in Computational Optimization and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:coopap:v:68:y:2017:i:3:d:10.1007_s10589-017-9935-4