STFLS: A Heuristic Method for Static and Transportation Facility Location Allocation in Large Spatial Datasets

  • Authors:
  • Wei Gu;Xin Wang;Liqiang Geng

  • Affiliations:
  • Department of Geomatics Engineering, University of Calgary, Calgary, Canada;Department of Geomatics Engineering, University of Calgary, Calgary, Canada;NRC Institute for Information Technology, Fredericton, Canada

  • Venue:
  • Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
  • Year:
  • 2009

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Abstract

This paper solves a static and transportation facility location allocation problem defined as follows: given a set of locations Loc and a set of demand objects D located in Loc , the goal is to allocate a set of static facilities S and a set of transportation facilities T to the locations in Loc , which minimizes both the average travelling distance from D to S and the maximum transportation travelling distance between D and S through T . The problem is challenging because two types of facilities are involved and cooperate with each other. In this paper, we propose a static and transportation facility location allocation algorithm, called STFLS, to solve the problem. The method uses two steps of searching for static facility and transportation facility locations Experiments demonstrate the efficiency and practicality of the algorithm.