Engineering problems often involve many conflicting quality characteristics that must be optimized simultaneously. Engineers are required to select suitable design parameter values which provide better trade-off among all quality characteristics. Multiresponse optimization is one of the most essential tools for solving engineering problems involving multiple quality characteristics. Optimizing several quality characteristics when the quality characteristics are correlated makes the optimization process more complex. The aim of this research is to evaluate the performance of several existing multiresponse optimization methods and investigate their capabilities in dealing with correlated quality characteristics. This study also investigates the impact of uncertainty in terms of input parameter selection. A new multi-response optimization approach has been proposed for solving correlated quality characteristics. The proposed approach is compared with the existing methods and found more robust in terms dealing with uncertainty in target selection. The comparative study and application of the proposed approach is demonstrated by considering two examples from the literature having correlated quality characteristics.