An empirical study on parameter selection for multiobjective optimization algorithms using Differential Evolution

In this work, an empirical study on multiobjective optimization algorithms based on Differential Evolution (DE) algorithm is performed. The study focuses on getting good initial choices for evolutionary parameters for DE algorithm to tackle the multiobjective problem of PI controller tuning. This is an important issue in the field of control engineering, because the PI-PID controller remains a reliable digital solution for industrial processes. This study will bring an insight to the capabilities of a basic DE algorithm for multiobjective optimization, which can be the basis for more complex approaches using this evolutionary technique.