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Comparative study of four penalty-free constraint-handling techniques in structural optimization using harmony search
Engineering with Computers Pub Date : 2020-09-14 , DOI: 10.1007/s00366-020-01162-0
Hongyou Cao , Yupeng Chen , Yunlai Zhou , Shuang Liu , Shiqiang Qin

This study investigates the search capability, stability, and computational efficiency of four improved penalty-free constraint-handling techniques (CHTs), including the death penalty, the Deb rule, the filter method, and the mapping strategy, in structural optimization using harmony search (HS). The first three general-purpose CHTs have been improved by hybridizing with a structural analysis filter strategy to enhance their computational efficiency based on the characteristics of structural optimization and the solution updating rule of the HS. This study also has modified the mapping operator of the mapping strategy to handle size and shape optimization with Euler buckling constraints. Four numerical examples examine the performances of these CHTs. The comparative results show that the mapping strategy exhibits apparent superiority both in search capability and stability among the four. However, it also demands the most computational cost, and the improved Deb rule becomes the most competitive method while considering computational efficiency. The difference between the death penalty and the Deb rule method is that the feasible solution initialization process required by the death penalty method will deteriorate its computational efficiency in problems with small feasible space. The filter method always reserves some infeasible solutions to guide the search in the iteration process. However, its performances are inferior to the other three approaches in four benchmark problems.

中文翻译:

基于和声搜索的结构优化中四种无惩罚约束处理技术的比较研究

本研究调查了四种改进的无惩罚约束处理技术 (CHT) 的搜索能力、稳定性和计算效率,包括死刑、Deb 规则、过滤方法和映射策略,在使用和声搜索的结构优化中(HS)。根据结构优化的特点和HS的解更新规则,前三个通用CHT通过与结构分析过滤策略混合进行改进,以提高其计算效率。本研究还修改了映射策略的映射算子,以处理具有欧拉屈曲约束的尺寸和形状优化。四个数值示例检验了这些 CHT 的性能。对比结果表明,四种映射策略在搜索能力和稳定性上均表现出明显的优势。然而,它也需要最大的计算成本,在考虑计算效率的同时,改进的Deb规则成为最具竞争力的方法。死刑与Deb规则法的区别在于,死刑法所需的可行解初始化过程会降低其在可行空间小的问题上的计算效率。过滤方法总是保留一些不可行的解决方案来指导迭代过程中的搜索。然而,它在四个基准问题中的表现不如其他三种方法。在考虑计算效率的同时,改进的Deb规则成为最具竞争力的方法。死刑与Deb规则法的区别在于,死刑法所需的可行解初始化过程会降低其在可行空间小的问题上的计算效率。过滤方法总是保留一些不可行的解决方案来指导迭代过程中的搜索。然而,它在四个基准问题中的表现不如其他三种方法。在考虑计算效率的同时,改进的Deb规则成为最具竞争力的方法。死刑与Deb规则法的区别在于,死刑法所需的可行解初始化过程会降低其在可行空间小的问题上的计算效率。过滤方法总是保留一些不可行的解决方案来指导迭代过程中的搜索。然而,它在四个基准问题中的表现不如其他三种方法。死刑与Deb规则法的区别在于,死刑法所需的可行解初始化过程会降低其在可行空间小的问题上的计算效率。过滤方法总是保留一些不可行的解决方案来指导迭代过程中的搜索。然而,它在四个基准问题中的表现不如其他三种方法。死刑与Deb规则法的区别在于,死刑法所需的可行解初始化过程会降低其在可行空间小的问题上的计算效率。过滤方法总是保留一些不可行的解决方案来指导迭代过程中的搜索。然而,它在四个基准问题中的表现不如其他三种方法。
更新日期:2020-09-14
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