Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Abstract

A new heuristic approach for minimizing possibly nonlinear and non-differentiable con- tinuous space functions is presented. By means of an extensive testbed it is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. The new method requires few control variables, is robust, easy to use, and lends itselfvery well to parallel computation.