Multi-objective design optimisation of four-bar mechanisms using a hybrid ICA-GA algorithm

This work presents a novel approach to the multi-objective optimal design of four-bar mechanisms. Three conflicting objective functions are considered simultaneously, i.e., the tracking error (TE), the transmission angle deviation from 90° (TA) and the maximum angular velocity ratio (MAVR). To improve the convergence and the diversity of the results, an imperialist competitive algorithm is coupled with a genetic algorithm (ICA-GA) and it is used to solve this problem. A comparative study of the proposed ICA-GA shows that this method yields better results and more diverse results than other methods.