GISc to Enhance Facility Location Modeling and Problem Solution

Geographic Information Science to Enhance Facility Location Modeling and Problem Solution
Daoqin Tong, Geography and Regional Development, University of Arizona

Many government agencies and corporations face locational decisions,
such as where to locate fire stations, postal facilities, nature
reserves, computer centers, bank branches, etc. To reach such location
related decisions, geographical information systems (GIS) have been
essential for providing access to spatial data and analysis tools.
Moreover, geographic insights can be gained from GIS as it enables
capabilities for better reflecting problems of interest in location
modeling. One such model for regional coverage maximization will be
discussed in the talk. By accurately reflecting coverage mechanism, the
coverage discrepancy between what is modeled and the actual coverage is
significantly reduced. The new model can be viewed as an extension of
existing approaches, but also a generalization.
On the other hand, the resulting advanced model can be complex,
however, and hence computationally challenging to solve. This talk also
examines a new genetic algorithm as a heuristic for problem solution to
the model proposed above. The new heuristic innovatively incorporates
the geographical structure of the problem, enhancing overall
performance. Comparative application results demonstrate important
nuances of the new genetic algorithm, enabling high-quality solutions
to be identified in a reasonable amount of computing time. 

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