首页> 外文会议>Simulated evolution and learning >Constrained Engineering Design Optimization Using a Hybrid Bi-objective Evolutionary-Classical Methodology
【24h】

Constrained Engineering Design Optimization Using a Hybrid Bi-objective Evolutionary-Classical Methodology

机译:混合双目标进化经典方法对工程设计的约束

获取原文
获取原文并翻译 | 示例

摘要

Constrained engineering design optimization problems are usually computationally expensive due to non-linearity and non convexity of the constraint functions. Penalty function methods are found to be quite popular due to their simplicity and ease of implementation, but they require an appropriate value of the penalty parameter. Bi-objective approach is one of the methods to handle constraints, in which the minimization of the constraint violation is included as an additional objective. In this paper, constrained engineering design optimization problems are solved by combining the penalty function approach with a bi-objective evolutionary approach which play complementary roles to help each other. The penalty parameter is approximated using bi-objective approach and a classical method is used for the solution of unconstrained penalized function. In this methodology, we have also eliminated the local search parameter which was needed in our previous study.
机译:由于约束函数的非线性和非凸性,受约束的工程设计优化问题通常在计算上昂贵。惩罚函数方法由于其简单性和易于实现而非常受欢迎,但是它们需要惩罚参数的适当值。双目标方法是处理约束的方法之一,其中将约束违规的最小化作为附加目标。本文通过将惩罚函数法与双目标进化法相结合来解决受限的工程设计优化问题,两者互为补充。惩罚参数使用双目标方法进行近似,并且经典方法用于无约束惩罚函数的求解。在这种方法中,我们还消除了先前研究中所需的局部搜索参数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号