A preference choice model for the new product design problem

The design of new products is a matter of great importance that can directly affect profitability and competitiveness in modern companies. For this reason, the selection of a final product design needs to consider at least four factors of importance: anticipated market demand for the product design, preference heterogeneity among consumers, decision-maker preferences, and fuzzy preference information in the design criteria. This paper proposes a frequency-based preference choice model that considers all the above factors and can be used with algorithms that solve the optimal product design problem using the share of preference frequency criterion. The choice model introduced in this paper is based on the multicriteria outranking approach, and its predictive accuracy is optimized with genetic algorithms. The proposed genetic algorithm is compared with Interior Point OPTimizer, a software package for large-scale non-linear optimization. The experiment results demonstrate that the proposed method achieves near-optimal solutions in reasonable computational time and significantly outperforms the runtime compared algorithm.