Merge of Evolutionary Computation with Gradient Based Method for Optimization Problems

The paper describes an optimization method which combines advantages of both evolutionary computation and gradient based methods. The proposed method follows the general concept of evolutionary computation, but uses an approximated gradient for generating subsequent populations. The gradient is not explicitly computed, but is instead estimated using minimum solutions from neighboring populations. Experimental data shows that the proposed method is not only robust, but is also comparable to gradient methods with respect to speed of convergence.