Finding the set of optimal architectures is an important challenge for the designer who uses the Model-Based System Engineering with SysML. The paper discusses the application of techniques to solve a Constraint Satisfaction Multi-criteria Optimization Problem (CSMOP) obtained from a SysML model. In this paper, we present our methodology and propose several stereotypes for model variability, including continuous and discrete variables. Then we define a new parametric diagram usage for context modeling optimization. From this optimization context and model variability, it is possible to generate a problem description file for the PyOpt optimization framework. Finally a case study combining optical and electronic parameters illustrates the methodology with numerical results.