Knowledge-based approaches to self-adaptation in cultural algorithms
Knowledge-based approaches to self-adaptation in cultural algorithms
Knowledge-based solution to dynamic optimization problems using cultural algorithms
Knowledge-based solution to dynamic optimization problems using cultural algorithms
Knowledge-based function optimization using fuzzy culturalalgorithms with evolutionary programming
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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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 chaosbased 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.