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In this paper, an implicit iterative algorithm is developed to obtain the unique positive definite solution of the generalized algebraic Riccati matrix equation. For this proposed algorithm, there exisits a tuning parameter which can be chosen such that this algorithm achieves better convergence performance. Some convergence results are given for the proposed algorithm. Moreover, an approach is also...
Because have very high ability of overall situation searching and convergence speed, show excellently in keeping solution variety, the niche genetic algorithm(NGA) is widely used to solving various kinds of combination optimization problem, but the traditional niche genetic algorithm(T-GA) have the problem that the discrimination standard of Euclidean distance between two individuals is not development...
Memetic algorithms (MAs) are widely recognized to have better convergence capability than their conventional counterparts. Due to its good robustness and universality, differential evolution (DE) has been frequently used as the global search method in MAs. However, on account of the limited performance of the conventional local search operators, the performance of previous DE-related MAs still needs...
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle...
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. In this paper, a two-stage based ensemble optimization evolutionary algorithm (EOEA) is designed to handle LSGO problems. The performance of EOEA is evaluated on the test functions provided by the LSGO competition of IEEE Congress...
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