Work place: Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria
E-mail: Jampour@IEEE.org
Website:
Research Interests: Artificial Intelligence
Biography
Mahdi Jampour is Ph. D. student in Institute for Computer Graphics and Vision (ICG) at Graz University of Technology (Graz, Austria). He got his B.S. in Computer Science from Shahid Bahonar University of Kerman in 2006 and got M.Sc. from Islamic Azad University of Mashhad in Artificial Intelligence (2009). He has received a scholarship from Iran Ministry of Science, Research and Technology to continue his studies towards Ph.D. (2010). His research interests are Computer Vision and Application of Chaos theory. He is a member of IEEE and IACSIT and also editorial member of some international journals.
By Reza Ebrahimzadeh Mahdi Jampour
DOI: https://doi.org/10.5815/ijisa.2013.05.03, Pub. Date: 8 Apr. 2013
Very recently evolutionary optimization algorithms use the Genetic Algorithm to improve the result of Optimization problems. Several processes of the Genetic Algorithm are based on 'Random', that is fundamental to evolutionary algorithms, but important defections in the Genetic Algorithm are local convergence and high tolerances in the results, they have happened for randomness reason. In this paper we have prepared pseudo random numbers by Lorenz chaotic system for operators of Genetic Algorithm to avoid local convergence. The experimental results show that the proposed method is much more efficient in comparison with the traditional Genetic Algorithm for solving optimization problems.
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