Use of distributed data sources in facility location

  • Authors:
  • Jnis Grabis;Charu Chandra;Jnis Kampars

  • Affiliations:
  • Institute of Information Technology, Riga Technical University, Kalku 1, Riga LV-1658, Latvia;College of Business University of Michigan-Dearborn, 19000 Hubbard Drive, Dearborn, MI 48126, USA;Institute of Information Technology, Riga Technical University, Kalku 1, Riga LV-1658, Latvia

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2012

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Abstract

Facility location decisions are usually determined by cost and coverage related factors although empirical studies show that such factors as infrastructure, labor conditions and competition also play an important role in practice. The objective of this paper is to develop a multi-objective facility location model accounting for a wide range of factors affecting decision-making. The proposed model selects potential facilities from a set of pre-defined alternative locations according to the number of customers, the number of competitors and real-estate cost criteria. However, that requires large amount of both spatial and non-spatial input data, which could be acquired from distributed data sources over the Internet. Therefore, a computational approach for processing input data and representation of modeling results is elaborated. It is capable of accessing and processing data from heterogeneous spatial and non-spatial data sources. Application of the elaborated data gathering approach and facility location model is demonstrated using an example of fast food restaurants location problem.