Abstract
Model transformation stands for an important issue to manipulate models in the model-driven engineering approach. Indeed, it consists of a set of transformation rules describing how a construct from a source model can be transformed to one or several ways in the target model. Though alternative target models may be equivalent from the functional perspective, they may differ from the non-functional perspective. Besides, they do not satisfy the same usability aspects. One of the main challenges of the transformation process is identifying the alternative transformation that generates a highly usable target model according to a set of desired usability attributes. Our research work addresses this issue by combining the power of model transformations engine and search techniques. Specifically, the proposed approach defines model transformation as a usability optimization problem. It allows the search of the optimal alternative transformation from a large search space taking into account an agreed usability model and using a metaheuristic search algorithm.