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Abstract To solve non-probabilistic reliability, the improved one-dimensional optimization algorithm can be easily used, which, however, only searches part of the probable failure points. The global optimization method, on the other hand, although capable of searching all the probable failure points, requires a large amount of calculation. In view of such situation, an improved global optimization method is proposed in this study by combining the improved one-dimensional optimization algorithm with the global optimization method. The presented method possesses the advantages of both the improved one-dimensional optimization algorithm and the global optimization method, by means of which, the values of variables are determined based on the monotonicity of variables. Without losing any probable failure points, this method is contributive to reducing the number of extreme point equations, lowering the computational complexity, and improving the computational efficiency. The effectiveness and feasibility of the presented method are verified by examples.
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Received: 28 April 2017
Published: 06 December 2017
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2018, Vol. 39 
