2024 Volume 15 Issue 2 Pages 404-420
Multi-objective Optimization Problems (MOPs) attempt to find solutions simultaneously by minimizing or maximizing multiple objective functions in a trade-off relationship. As a solution method for MOPs, Cooperative Multi-Objective Differential Evolution (CMODE) has been proposed. Although the CMODE shows good performance for the MOPs, this method sometimes found partially biased solutions in a single trial. To solve this problem, we have already proposed an improved CMODE method. In this study, we comprehensively evaluate the performance of the improved method on low-dimensional and high-dimensional benchmark problems using various evaluation measures. Numerical results show that the improved method exhibits a small inverted generational distance for all low-dimensional and some high-dimensional benchmark problems, as compared to conventional solution methods.