An easy‐to‐implement differential evolution approach for multi‐objective optimizations

To present and validate a new differential evolution (DE) method for multi‐objective optimization method.

A new selection scheme was designed to replace the existing one in DE to enable DE applicable to either single objective or multi‐objective optimizations.

The new method was validated with three simple multi‐objective optimization problems. The simulation results show that the approach is capable of generating an approximated Pareto‐front for each selected problem. The new DE method was used to optimize a prototype air mixer subject to two objective functions to be minimized. The results demonstrate that the new DE approach can handle this practical multi‐objective problem successfully.

The new method is an easy‐to‐implement evolutionary method and has the potential for application for any complicated engineering optimizations.