Car Centres Placement Problem

Abstract

Deciding on where to locate the next retail outlet is a problem with a long and distinguished history beginning with the early work of Hotelling (1929) and extended by Huff (1964). The basic idea is to view potential customers as sources of purchasing power while a retail store possesses attractiveness thus creating an interacting particle model.

Here, we address the issue of where to locate a new car center based on a limited dataset. A method for distilling aggregate population information down to sub-regions is developed to provide estimates that feed into the optimization algorithm.
Two measures were used in the optimization: (i) total market share and (ii) total attractiveness. Total market share optimization is found to lead to placing the center close to competitors, while total attractiveness optimization is found to lead to placing the center closer to centroid of the population.