To avoid failures in the marketplace, the control of the risks in product innovation and the reduction of the innovation cycles require fast and valid assessments from customers. An interactive genetic algorithm (IGA) is proposed for eliciting users' perceptions about the shape of a product, in order to stimulate creativity and to identify design trends. Interactive users' assessment tests are conducted on virtual products to capture and analyze users' responses. The IGA is interfaced with Computer Aided Design (CAD) software (CATIA V5) to create sets of parameterized designs in real time, which are presented iteratively by a graphical interface to the users for evaluation. After a description of the IGA, a study on the convergence of the IGA is presented. The convergence varies, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 45 users on the application case, a dashboard, put forward by Renault. The implementation of the perceptive tests and the analysis of the results are described using hierarchical ascendant classification (HAC) and multivariate analysis. This paper shows how the results of tests using IGA can be used to elicit user perception and to detect design trends.

To avoid flops, the control of the risks in product innovation and the reduction of the innovation cycles require valid and fast customer’s assessments. An Interactive Genetic algorithm is proposed for eliciting user’s perceptions concerning the shape of a product, in order to stimulate creativity and detecting design trends. Interactive users’ assessment tests are conducted on virtual products, for capturing and analyzing users’ responses. The IGA is interfaced with a CAD software (CATIA V5) and allows the creation in real time of a set of parameterized designs, which are presented iteratively by a graphical interface to the user for evaluation. After a description of the IGA, we present a study on the convergence of the IGA, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 20 users on a particular product, table glasses. We describe the implementation of the perceptive tests and an analysis of the results. These results show how the IGA can be used to elicit user perception and detecting design trends.

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