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Modelling and Simulation in Engineering
Volume 2011, Article ID 239743, 6 pages
Research Article

Chaotic-Search-Based Cultural Algorithm for Solving Unconstrained Optimization Problem

Jianjia He1,2 and Fuyuan Xu1,2

1Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
2Center for Supernetworks Research (China), Shanghai 200093, China

Received 16 March 2011; Revised 25 May 2011; Accepted 29 June 2011

Academic Editor: Farouk Yalaoui

Copyright © 2011 Jianjia He and Fuyuan Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


For premature convergence and instability of cultural algorithm in solving function optimization problem, based on cultural algorithm and chaos search optimization, a chaos cultural algorithm (CCA) is proposed. The algorithm model consists of a chaos-based population space and a knowledge-storing belief space, uses normative knowledge and situational knowledge for chaos search and chaos perturbation, respectively, effectively avoids premature convergence of cultural algorithm, and overcomes chaos search optimization's sensitivity to initial values and poor efficiency. Test results show that this algorithm is strong in global search and has good performance in searching efficiency, precision, and stability, especially in solving high-dimensional optimization problem.