Decision-making is one of the contemporary issues in this modern era due to the interaction of risk and uncertainties in every aspect of the daily lives of human beings. Accordingly, solving practical optimization problems tends to be more challenging. The fundamental reason for this investigation is to explore an effective solution technique for multi-objective optimization problems (MOOPs) in an intuitionistic fuzzy environment (IFE) addressing the issue of determining proper violation parameters and tolerances to the objectives and constraints. The other significant characteristic of this study is the consideration of the decisionmaker's perspective, namely, optimistic, pessimistic and mixed views in the solution procedure. In the proposed method, compared to the existing study, the required number of iterations and stages are considerably reduced in solving intuitionistic fuzzy multi-objective optimization problems (IFMOOPs). Hence it has imperative advantages in solving complex real-world problems without much difficulty. One problem is solved to demonstrate the competency of the planned approach. A comparative analysis is also undertaken to ascertain the efficiency of the technique.