Game algorithm for reliability multi-objective design optimization based on adaptive behavior

被引：0
|
作者：
Feng J. [1 ,2 ]
Zhang J. [1 ,2 ]
Qiu J. [1 ,2 ]
机构：
[1] School of Reliability and Systems Engineering, Beihang University, Beijing
[2] Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2019年 / 25卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Adaptive behavior; Automobile brake; Game; Multi-objective optimization; Prduct design; Reliability; Strategy set;
D O I：
10.13196/j.cims.2019.03.020
中图分类号：
学科分类号：
摘要：
To solve the problem of reliability multi-objective design optimization, an adaptive behavior-based game algorithm was proposed by considering the dynamic characteristics of players' behaviors in the game process. Each design objective was regarded as a player, and the random design variable set was decomposed into the strategy sets of players through the fuzzy clustering analysis for the influence factors of random design variables about the objective functions. The adaptive behavior rule was established. Then, the behavior and the mapping relationship between the objective function and the payoff function of each player were adjusted before the new round of game based on the rule. After multi-round of games, the equilibrium solution was obtained based on the convergence criterion. The design results of the automobile brake indicated that the proposed algorithm had the higher calculation efficiency by comparing with the competitive game and cooperative game. © 2019, Editorial Department of CIMS. All right reserved.
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收藏
页码：736 / 742
页数：6
相关论文
共 23 条
  • [1] Wang J., Ma Y., Wang J., Applications of importance sampling based on Kriging metamodel in structural reliability analysis, Computer Integrated Manufacturing Systems, 22, 11, pp. 2643-2652, (2016)
  • [2] Fu C., Hu X., Yu H., Et al., Unified multidisciplinary reliability analysis by chi-squared distributions, Computer Integrated Manufacturing Systems, 23, 7, pp. 1439-1446, (2017)
  • [3] Garg H., Rani M., Sharma S.P., Et al., Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment, Expert Systems with Applications, 41, 7, pp. 3157-3167, (2014)
  • [4] Yu M., Shi B., Jiang Y., Application of physical programming in uncertainty optimization design of multi-disc wet brake, Transactions of the Chinese Society of Agricultural Machinery, 42, 4, pp. 22-26, (2011)
  • [5] Kogiso N., Kodama R., Toyoda M., Reliability-based multi-objective optimization using the satisficing trade-off method, Mechanical Engineering Journal, 1, 6, pp. 1-12, (2014)
  • [6] Wang R., Gu L., Gong C., A stratified sequencing multi-disciplinary reliability analysis method under random and interval uncertainty, Journal of Northwestern Polytechnical University, 34, 1, pp. 139-146, (2016)
  • [7] He L., Liu Q., Multi-objective Optimization Theory and Continuous Method, pp. 35-37, (2015)
  • [8] Juang C.H., Wang L., Reliability-based robust geotechnical design of spread foundations using multi-objective genetic algorithm, Computers and Geotechnics, 48, 4, pp. 96-106, (2013)
  • [9] Liu L., Xing C., Long T., Study of multi-objective trajectory optimization based on physical programming, Transactions of Beijing Institute of Technology, 33, 4, pp. 357-362, (2013)
  • [10] Xiao M., Shao X., Gao L., Et al., A new methodology for multi-objective multidisciplinary design optimization problems based on game theory, Expert Systems with Applications an International Journal, 42, 3, pp. 1602-1612, (2015)
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