中国机械工程 ›› 2010, Vol. 21 ›› Issue (13): 1609-1613.

• 材料工程 • 上一篇    下一篇

区间不确定多目标优化算法在薄板冲压成形中的应用研究

李方义;李光耀;李洪周;崔付刚
  

  1. 湖南大学汽车车身先进设计制造国家重点实验室,长沙,410082
  • 出版日期:2010-07-10 发布日期:2010-07-15
  • 基金资助:
    国家杰出青年科学基金资助项目(50625519);教育部长江学者和创新团队发展计划资助项目;湖南大学汽车车身先进设计制造国家重点实验室自主研究课题(60870005);科技部国际合作项目(2008DFB50020) 
    National Science Funds for Distinguished Young Scholars( No. 50625519);
    Supported by Program for Changjiang Scholars and Innovative Research Team in University;
    International Cooperation Program of Ministry of Science and Technology of China( No. 2008DFB50020)

Uncertain Multi-objective Optimization of Sheet Metal Forming Using Interval Method

Li Fangyi;Li Guangyao;Li Hongzhou;Cui Fugang
  

  1. State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha, 410082
  • Online:2010-07-10 Published:2010-07-15
  • Supported by:
     
    National Science Funds for Distinguished Young Scholars( No. 50625519);
    Supported by Program for Changjiang Scholars and Innovative Research Team in University;
    International Cooperation Program of Ministry of Science and Technology of China( No. 2008DFB50020)

摘要:

提出一种薄板冲压成形不确定多目标优化方法,该方法将冲压成形中的摩擦因数作为不确定参数,采用区间描述,以厚度不均最小和起皱最小为目标函数,以压边力和拉深筋阻力作为设计变量。基于非线性区间数值规划将不确定多目标优化问题转换为确定的多目标优化问题。采用Kriging近似模型提高优化效率,基于多目标遗传算法和序列二次规划算法的混合优化算法取得Pareto解集。应用算例说明了该算法的有效性。

关键词:

Abstract:

An uncertain multi-objective optimization method was suggested to solve the optimization problem of sheet metal forming. The friction coefficient was regarded as the uncertain coefficient, which was treated as an interval. The binder force and drawbead restraining force were selected as the design variables, and the objectives were to minimize thickness non-uniform and wrinkle. Through a nonlinear interval number programming method, the uncertain optimization problem was converted into a deterministic two-objective optimization problem. The Kriging approximation model was constructed to improve the efficiency. The hybrid optimization algorithm based on multi-objective genetic algorithm and sequential quadratic programming algorithm was adopted to obtain the Pareto set. The results of the example demonstrate the efficiency of the presented method.

Key words: uncertain multi-objective optimization;sheet metal forming, nonlinear interval number programming, Kriging approximation model

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