Some Proposals for Stochastic Facility Location Models
Abstract
The static facility location model with a spatial interaction-based allocation rule has been first introduced by Coelho and Wilson (1976). The main interest in introducing a spatial interaction-based allocation rule lies in the more realistic trip patterns that result from its use, which in many cases seem to fit the actual data on customer choice better than the simple nearest-facility allocation rule.
A further step towards more realistic models of customer behavior is the introduction of stochastic features, describing both the amount of total demand for facilities and the trip pattern of the customers. In this paper the usefulness of stochastic programming tools to formulate and solve such problems is explored, and some simple, but easily generalizable applied examples are given. Both numerical techniques and exact analytical methods are outlined, and some issues for further research are proposed.
A further step towards more realistic models of customer behavior is the introduction of stochastic features, describing both the amount of total demand for facilities and the trip pattern of the customers. In this paper the usefulness of stochastic programming tools to formulate and solve such problems is explored, and some simple, but easily generalizable applied examples are given. Both numerical techniques and exact analytical methods are outlined, and some issues for further research are proposed.