Nature-Inspired Computation based on orthogonal intelligence optimization

In order to overcome premature convergence and low performance of existing intelligent optimization algorithms, a algorithm of Nature-Inspired Computation based on orthogonal intelligent optimization is put forward for continue and discrete function in this paper. The orthogonal intelligent optimization based on the variance analysis and variance ratio analysis of orthogonal design is developed, which provides further searching direction and searching range of orthogonal experiment. Because the characteristic of orthogonal design is easy to find an interval that contains the best solution in one arrayed calculation, the algorithm of orthogonal intelligent optimization based on the analysis of variance ratio is able to reuse in the optimization searching. The algorithm of Nature-Inspired Computation based on orthogonal intelligent optimization has less calculation amount, shorter searching time, more rapid speed and higher accuracy of optimization searching. The simulation analysis for nonlinear programming problem is performed successfully. The simulation result shows that this algorithm is much better than existing algorithms of Nature-Inspired Computation.