Solving global optimal problems by using a dynamical evolutionary algorithm

Abstract

We introduce a new dynamical evolutionary algorithm and use it to solve global optimal problems. A brief theoretical explanation for this algorithm is obtained from statistical mechanics. The algorithm has been evaluated numerically using a wide set of test functions which are nonlinear, multimodal and multidimensional. Numerical results show that the algorithm has the potential to obtain a global optimum or more accurate solutions than other methods for hard problems.

Cite this paper

@article{Li2002SolvingGO, title={Solving global optimal problems by using a dynamical evolutionary algorithm}, author={Yuanxiang Li and Xiufen Zou}, journal={Fifth International Conference on Algorithms and Architectures for Parallel Processing, 2002. Proceedings.}, year={2002}, pages={170-173} }