Abstract: This study proposes a multi-objective cascade control approach to tune the various controllers employed in the cascade control loop. Most of the modern cascade loops require separate tuning of primary and secondary controllers and hence the design task becomes complicated. Non-dominated Sorting Genetic Algorithm (NSGA-II) and Non-dominated Sorting Particle Swarm Optimization algorithm (NSPSO) based multiobjective approaches are employed in the design to fine tune the controller parameters of both primary and secondary loop. Inner loop comprises of flow process and the outer loop comprises of level process. The process considered in this study is highly non-linear with varying time delay and provides a challenging test bed for most of the modern control problems. Experimental results confirm that a multi-objective, paretobased NSPSO search gives a better performance for regulatory process when compared to NSGA-II. Finally, multiobjective optimization using NSPSO for the level process are compared with NSGA-II and the former exhibit good disturbance rejection capability which is a primary factor considered in cascade control.