Evolutionary algorithms with deterministic mutation operators used for the optimization of the trajectory of a four-bar mechanism Original Research Article

In this paper, we propose an Evolutionary Algorithm (EA) with a deterministic mutation operator which is a combination of EA with the Broyden, Fletcher, Goldfarb and Shanno (BFGS) method. The advantages of both optimization algorithms are retained and interconnected. The proposed algorithm shows faster convergence as well as increased reliability in the search for the global optimum. Results referring to the Fletcher and Powel test function in comparison with EA (Evolution Strategies, Evolutionary Programming, and Genetic Algorithms), provide sufficient indication for the performance of the new method. Finally, the proposed method is successfully implemented for the trajectory optimization of a four-bar mechanism.