This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum structures.These structures,commonly encounter...This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum structures.These structures,commonly encountered in engineering applications,often involve complex objective and constraint functions that cannot be readily expressed as explicit functions of the design variables.As a result,sequential approximation techniques have emerged as the preferred strategy for addressing a wide array of topology optimization challenges.Over the past several decades,topology optimization methods have been advanced remarkably and successfully applied to solve engineering problems incorporating diverse physical backgrounds.In comparison to the large-scale equation solution,sensitivity analysis,graphics post-processing,etc.,the progress of the sequential approximation functions and their corresponding optimizersmake sluggish progress.Researchers,particularly novices,pay special attention to their difficulties with a particular problem.Thus,this paper provides an overview of sequential approximation functions,related literature on topology optimization methods,and their applications.Starting from optimality criteria and sequential linear programming,the other sequential approximate optimizations are introduced by employing Taylor expansion and intervening variables.In addition,recent advancements have led to the emergence of approaches such as Augmented Lagrange,sequential approximate integer,and non-gradient approximation are also introduced.By highlighting real-world applications and case studies,the paper not only demonstrates the practical relevance of these methods but also underscores the need for continued exploration in this area.Furthermore,to provide a comprehensive overview,this paper offers several novel developments that aim to illuminate potential directions for future research.展开更多
为快速实现波达方向角(DOA:Direction Of Arrival)的精确估计,提出了应用序列二次规划(SQP:Sequence Quadratic Program)的最大似然DOA估计算法。给出了用于DOA估计的最大似然函数,将参数估计问题转化为非线性函数优化问题;并利用SQP优...为快速实现波达方向角(DOA:Direction Of Arrival)的精确估计,提出了应用序列二次规划(SQP:Sequence Quadratic Program)的最大似然DOA估计算法。给出了用于DOA估计的最大似然函数,将参数估计问题转化为非线性函数优化问题;并利用SQP优化算法对似然函数的求解进行优化,得到DOA的估计值。仿真结果表明,该算法可用较少的计算时间实现对似然函数的优化求解,同时保留了最大似然估计的渐进无偏估计性能,与遗传算法、粒子群算法相比,不仅具有更快的寻优速度,而且具有更高的收敛精度。展开更多
基金financially supported by the National Key R&D Program (2022YFB4201302)Guang Dong Basic and Applied Basic Research Foundation (2022A1515240057)the Huaneng Technology Funds (HNKJ20-H88).
文摘This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum structures.These structures,commonly encountered in engineering applications,often involve complex objective and constraint functions that cannot be readily expressed as explicit functions of the design variables.As a result,sequential approximation techniques have emerged as the preferred strategy for addressing a wide array of topology optimization challenges.Over the past several decades,topology optimization methods have been advanced remarkably and successfully applied to solve engineering problems incorporating diverse physical backgrounds.In comparison to the large-scale equation solution,sensitivity analysis,graphics post-processing,etc.,the progress of the sequential approximation functions and their corresponding optimizersmake sluggish progress.Researchers,particularly novices,pay special attention to their difficulties with a particular problem.Thus,this paper provides an overview of sequential approximation functions,related literature on topology optimization methods,and their applications.Starting from optimality criteria and sequential linear programming,the other sequential approximate optimizations are introduced by employing Taylor expansion and intervening variables.In addition,recent advancements have led to the emergence of approaches such as Augmented Lagrange,sequential approximate integer,and non-gradient approximation are also introduced.By highlighting real-world applications and case studies,the paper not only demonstrates the practical relevance of these methods but also underscores the need for continued exploration in this area.Furthermore,to provide a comprehensive overview,this paper offers several novel developments that aim to illuminate potential directions for future research.
文摘为快速实现波达方向角(DOA:Direction Of Arrival)的精确估计,提出了应用序列二次规划(SQP:Sequence Quadratic Program)的最大似然DOA估计算法。给出了用于DOA估计的最大似然函数,将参数估计问题转化为非线性函数优化问题;并利用SQP优化算法对似然函数的求解进行优化,得到DOA的估计值。仿真结果表明,该算法可用较少的计算时间实现对似然函数的优化求解,同时保留了最大似然估计的渐进无偏估计性能,与遗传算法、粒子群算法相比,不仅具有更快的寻优速度,而且具有更高的收敛精度。
