%0 Journal Article
	%A L. Abdelmalek and  M. Zerikat and  M. Rahli
	%D 2007
	%J International Journal of Energy and Power Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 10, 2007
	%T Comparative study of the Genetic Algorithms and Hessians Method for Minimization of the Electric Power Production Cost
	%U https://publications.waset.org/pdf/16021
	%V 10
	%X In this paper, we present a comparative study of the
genetic algorithms and Hessian-s methods for optimal research of the
active powers in an electric network of power. The objective function
which is the performance index of production of electrical energy is
minimized by satisfying the constraints of the equality type and
inequality type initially by the Hessian-s methods and in the second
time by the genetic Algorithms. The results found by the application
of AG for the minimization of the electric production costs of power
are very encouraging. The algorithms seem to be an effective
technique to solve a great number of problems and which are in
constant evolution. Nevertheless it should be specified that the
traditional binary representation used for the genetic algorithms
creates problems of optimization of management of the large-sized
networks with high numerical precision.
	%P 1466 - 1473