基于新型自适应遗传算法的混合可靠性优化模型

doi:10.7527/S1000-6893.2018.22084

Abstract

Abstract: This paper presents a new adaptive genetic algorithm. The crossover and mutation operator curves are processed nonlinearly based on the logistic function and cosine function. The nonlinear adaptive adjustment of the crossover operator and mutation operator is realized. The new algorithm is used to solve the test function. The results show that the new algorithm can improve the convergence speed and accuracy and effectively jump out of local convergence, avoiding the occurrence of precocious phenomenon. Based on the new adaptive genetic algorithm, optimization of the mixed reliability model with censored random-fuzzy-interval variables is studied. A hybrid reliability optimization model is established based on the mixed reliability index. The optimization design of a transmission synchronizer system is conducted to show the applicability of the model proposed.

Key words: genetic algorithm, adaptation, crossover operator, mutation operator, hybrid reliability

CLC Number:

AN Hai, YAN Zhaoyi, SUN Peng, YIN Guiqiao. Hybrid reliability optimization model based on new adaptive genetic algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(7): 322084-322084.

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Hybrid reliability optimization model based on new adaptive genetic algorithm

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