Consumer choice in competitive location models

Abstract

The main aim of this thesis is the introduction of consumer store choice theories in the discrete competitive location models that have a maximum captured objective function. After the introduction and the literature review, chapter 3 analyses the importance of consumer behaviour with respect to distance in the optimality of locations obtained by a traditional discrete competitive location models. Once the distance attribute has been analysed, chapter 4 presents a methodology for determining which store attributes (other than distance) should be included in a new version of the Maximum Capture Discrete Competitive Location models to the retail sector, as well as how these parameters ought to be reflected. The revealed preference store choice model use to define this methodology is the Multiplicative Competitive Interaction model. The methodology is tested to the supermarket sector in two different scenarios: Barcelona and Milton Keynes . Chapter 5 presents the New Chance Constrained Maximum Capture Location Problem. , which is a maximum capture model that takes into account the store-choice theories and has an stochastic threshold constraint. Finally, chapter 6 presents the algorithms developed to solved the models presented in this thesis (chapter 3 and chapter 5). Basically, this chapter presents the formulation development and the computational experience, for a two metaheuristics. These are based in three metaheuristics: GRASP, Ant System and TABU Search.