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Methodological and empirical issues in market segmentation: a comparison of the formal and the bio-mimetic methods

Jacques-Marie Aurifeille. University of la Réunion

Marie-Pierre Pinto. Université de Limoges

Abstract

A bio-mimetic approach of multiple goal problem solving is proposed. The approach relies on the stochastic ope-rators (reproduction, selection) of the Genetic Algorithms (GA). The method is presented in the case of a three-goal management problem: market segmen-tation and compared empirically with the two-goal bio-mimetic algorithm (TYPREN) from which it is derived and with the statistical Regression Mixture Model (GLIMMIX).

Keywords: Segmentation, Multiple Goal, Genetic Algorithm, Heuristic Operator, Cluster-Wise Regression, Automatic Interaction Detection, Regression Mixture Models

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