The work aims to enhance the designers' recognition on geometric attributes of consumer electronic products, improve the users' perception of product appearance affordance and provide reference for the early shape design of related products by evaluating the affordance quality of products and establishing the mapping relationship between them and design parameters. Firstly, based on the affordance theory and the Improved Archive-based Micro Genetic Algorithm (AMGA2), an optimization platform was designed. Secondly, taking the compact digital camera as a concrete research example, the mapping relationship between affordance and design parameters was quantitatively studied by Binary Logistic Regression Analysis. Designers could adjust the design parameters through the simulation and prediction of the regression equation, thus increasing or decreasing the specific affordance of products and improving users' perception of product affordance quality. Finally, the design optimization platform ABIGA, has helped the evolution of different shape solutions, hoping that these solutions can effectively inspire relevant designers in early camera shape design.