An efficient dynamical evolutionary algorithm for global optimization
X Zou, Y Li, L Kang, Z Wu - International journal of computer …, 2003 - Taylor & Francis
X Zou, Y Li, L Kang, Z Wu
International journal of computer mathematics, 2003•Taylor & FrancisIn this paper, we introduce a new dynamical evolutionary algorithm (DEA) that aims to find
the global optimum and give the theoretical explanation from statistical mechanics. The
algorithm has been evaluated numerically using a wide set of test functions which are
nonlinear, multimodal and multidimensional. The numerical results show that it is possible to
obtain global optimum or more accurate solutions than other methods for the investigated
hard problems.
the global optimum and give the theoretical explanation from statistical mechanics. The
algorithm has been evaluated numerically using a wide set of test functions which are
nonlinear, multimodal and multidimensional. The numerical results show that it is possible to
obtain global optimum or more accurate solutions than other methods for the investigated
hard problems.
In this paper, we introduce a new dynamical evolutionary algorithm (DEA) that aims to find the global optimum and give the theoretical explanation from statistical mechanics. The algorithm has been evaluated numerically using a wide set of test functions which are nonlinear, multimodal and multidimensional. The numerical results show that it is possible to obtain global optimum or more accurate solutions than other methods for the investigated hard problems.
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