Construction Line Algorithms for the Connection Location-Allocation Problem

Martin Bischoff () and Yvonne Bayer
Additional contact information
Martin Bischoff: University of Erlangen-Nuremberg
Yvonne Bayer: University of Erlangen-Nuremberg

A chapter in Operations Research Proceedings 2007, 2008, pp 345-350 from Springer

Abstract: Abstract In the connection location-allocation problem we are given a set of material flows between pairs of existing facilities each of which must be routed through a connection facility. The objective is to minimize the total transportation costs by locating a given number of connections and allocating the flows accordingly. For this problem many properties and solution methods of the well-known facility location-allocation problem can be transferred, among others the construction line algorithm, an exact solution method based on discretization results under polyhedral gauge distances. We have implemented construction line algorithms for the connection location-allocation problem without restrictions as well as in the presence of forbidden regions or barriers. We considered various distance functions, ranging from the Manhattan distance to mixed polyhedral gauge distances and applied hull properties to further reduce the dominating set.

Keywords: Location Problem; Manhattan Distance; Block Norm; Weber Problem; Total Transportation Cost (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:oprchp:978-3-540-77903-2_53

Ordering information: This item can be ordered from
http://www.springer.com/9783540779032

DOI: 10.1007/978-3-540-77903-2_53

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().