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

电子电气工程与控制

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基于新型自适应遗传算法的混合可靠性优化模型

安海, 阎朝一, 孙鹏, 尹瑰巧

哈尔滨工程大学航天与建筑工程学院, 哈尔滨 150001

收稿日期:2018-02-06 修回日期:2018-03-23 出版日期:2018-07-15 发布日期:2018-03-23
通讯作者: 安海 E-mail:anhai@hrbeu.edu.cn
基金资助:
黑龙江省自然科学基金（A201311）

Hybrid reliability optimization model based on new adaptive genetic algorithm

AN Hai, YAN Zhaoyi, SUN Peng, YIN Guiqiao

College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China

Received:2018-02-06 Revised:2018-03-23 Online:2018-07-15 Published:2018-03-23
Supported by:
Natural Science Foundation of Heilongjiang Province (A201311)

摘要/Abstract

摘要： 提出一种新型的自适应遗传算法。结合Logistic函数和余弦函数，对交叉、变异算子曲线进行非线性化处理，实现了交叉算子和变异算子的非线性自适应调整。用新算法求解测试函数，结果表明新算法能够提高收敛速度和精确度，有效地跳出局部收敛，避免早熟现象发生。并基于提出的新型自适应遗传算法，研究了截尾随机-模糊-区间变量的混合可靠性模型的优化问题，建立了以混合可靠性指标作为优化约束条件的混合可靠性优化模型。以某型飞机变速箱同步器系统的优化设计为例，验证了该模型在工程应用中的有效性。

关键词: 遗传算法, 自适应, 交叉算子, 变异算子, 混合可靠性

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

中图分类号:

安海, 阎朝一, 孙鹏, 尹瑰巧. 基于新型自适应遗传算法的混合可靠性优化模型[J]. 航空学报, 2018, 39(7): 322084-322084.

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.

参考文献

[1] HOLLAND J H. Adaptation in natural and artificial systems[M]. Cambridge:MIT Press, 1992:126-137.
[2] MOON J, LINNINGER A A. A hybrid sequential niche algorithm for optimal engineering design with solution multiplicity[J]. Computers & Chemical Engineering, 2009, 33(7):1261-1271.
[3] PASZKOWICZ W. Properties of a genetic algorithm equipped with a dynamic penalty function[J]. Computational Materials Science, 2009, 45(1):77-83.
[4] HWANG S F, HE R S. Improving real-parameter genetic algorithm with simulated annealing for engineering problems[J]. Advances in Engineering Software, 2006, 37(6):406-418.
[5] SRINIVAS M, PATNAIK L M. Adaptive probabilities of crossover and mutation in genetic algorithms[J]. IEEE Transactions on Systems Man & Cybernetics, 1994, 24(4):656-667.
[6] 王小平, 曹立明. 遗传算法——理论、应用与软件实现[M]. 西安:西安交通大学出版社, 2002:73-76. WANG X P, CAO L M. Genetic algorithm-Theory, application and software implementation[M]. Xi'an:Xi'an Jiao Tong University Press, 2002:73-76(in Chinese).
[7] 任子武, 伞冶. 自适应遗传算法的改进及在系统辨识中应用研究[J]. 系统仿真学报, 2006, 18(1):41-43. REN Z W, SAN Y. Improved adaptive genetic algorithm and its application research in parameter identification[J]. Journal of System Simulation, 2006, 18(1):41-43(in Chinese).
[8] 石山, 励庆孚, 王兴华. 基于自适应遗传算法的无刷直流电机的优化设计[J]. 西安交通大学学报, 2002, 36(12):1215-1218. SHI S, LI Q F, WANG X H. Design optimization of brushless direct current motor based on adaptive genetic algorithm[J]. Journal of Xi'an Jiaotong University, 2002, 36(12):1215-1218(in Chinese).
[9] 邝航宇, 金晶, 苏勇. 自适应遗传算法交叉变异算子的改进[J]. 计算机工程与应用, 2006, 42(12):93-96. KUANG H Y, JIN J, SU Y.Improving crossover and mutation for adaptive genetic algorithm[J].Computer Engineering and Applications, 2006, 42(12):93-96(in Chinese).
[10] LI Q, HE W H, JIANG H H, et al. A study on image segmentation by an improved adaptive algorithm[C]//International Conference on Machine Learning and Cybernetics. Piscataway,NJ:IEEE Press, 2007:1570-1573.
[11] 张玉萍. 自适应遗传算法的研究及应用[D]. 哈尔滨:哈尔滨工业大学, 2009. ZHANG Y P.Research and application of the auto-adapted genetic algorithm[D]. Harbin:Harbin Institute of Technology, 2009(in Chinese).
[12] YE Z, LI Z, XIE M. Some improvements on adaptive genetic algorithms for reliability-related applications[J]. Reliability Engineering & System Safety, 2010, 95(2):120-126.
[13] 陈超. 自适应遗传算法的改进研究及其应用[D]. 广州:华南理工大学, 2011. CHENG C. The improved research and application of adaptive genetic algorithm[D]. Guangzhou:South China University of Technology, 2011(in Chinese).
[14] JOSẼ-REVUELTA L M S. A new adaptive genetic algorithm for fixed channel assignment[J]. Information Sciences, 2007, 177(13):2655-2678.
[15] BINGUL Z. Adaptive genetic algorithms applied to dynamic multiobjective problems[J]. Applied Soft Computing, 2007, 7(3):791-799.
[16] LUO Y, KANG Z, LI A. Structural reliability assessment based on probability and convex set mixed model[J]. Computers & Structures, 2009, 87(21):1408-1415.
[17] JIANG C, LONG X Y, HAN X, et al. Probability-interval hybrid reliability analysis for cracked structures existing epistemic uncertainty[J]. Engineering Fracture Mechanics, 2013, 112-113(11):148-164.
[18] AN H, ZHOU L, SUN H. Structural hybrid reliability index and its convergent solving method based on random-fuzzy-interval reliability model[J]. Advances in Mechanical Engineering, 2016, 8(8):1-13.
[19] YANG X, LIU Y, ZHANG Y, et al. Probability and convex set hybrid reliability analysis based on active learning Kriging model[J]. Applied Mathematical Modelling, 2015, 39(14):3954-3971.
[20] WU D, GAO W, TIN-LOI F, et al. Probabilistic interval limit analysis for structures with hybrid uncertainty[J]. Engineering Structures, 2016, 114:195-208.
[21] 周凌, 李艳辉. 基于截尾概率-非概率混合模型的可靠性优化算法[J]. 航空学报, 2017, 38(1):220216. ZHOU L, LI Y H. Reliability based optimization algorithm using hybrid mode with truncated probability and non-probability[J]. Acta Aeronautica et Astronautica Sinica, 2017,38(1):220216(in Chinese).
[22] 周凌, 安伟光, 贾宏光. 超椭球凸集合可靠性综合指标定义与求解算法[J]. 航空学报, 2011, 32(11):2025-2035. ZHOUL, AN W G, JIA H G. Definition and solution of reliability comprehensive index of super-ellipsoid convex set[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(11):2025-2035(in Chinese).
[23] 安伟光.结构系统可靠性和基于可靠性的优化设计[M]. 北京:国防工业出版社, 1997:178-183. AN W G. Structural system reliability and reliability-based optimization design[M]. Beijing:National Defend Industry Press, 1997:178-183(in Chinese).

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于新型自适应遗传算法的混合可靠性优化模型

Hybrid reliability optimization model based on new adaptive genetic algorithm

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