<p>Scalarization methods and the generalized Tchebycheff norm have consistently played an extremely important role in the field of multi-objective optimization. In this paper, based on the research of scalarization methods for multi-objective optimization problems and combined with robust optimization theory, we propose a robust generalized Tchebycheff scalarization method suitable for uncertain multi-objective optimization problems. By proposing a novel combined scalarization framework integrating generalized Tchebycheff norm with slack/surplus variables, we establish the necessary and sufficient conditions for robust (weakly, properly) efficient solutions. This research enriches the scalarization theory of uncertain multi-objective optimization problems and provides a theoretical foundation for further studies in related fields.</p>