A novel approach to exploiting the log-convex structure present in many design problems is developed by modifying the classical Sequential Quadratic Programming (SQP) algorithm. The modified algorithm, Logspace Sequential Quadratic Programming (LSQP), inherits some of the computational efficiency exhibited by log-convex methods such as Geometric Programing and Signomial Programing, but retains the the natural integration of black box analysis methods from SQP. As a result, significant computational savings is achieved without the need to invasively modify existing black box analysis methods prevalent in practical design problems. In the cases considered here, the LSQP algorithm shows a 40-70% reduction in number of iterations compared to SQP.

中文翻译：

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用于设计优化的对数空间顺序二次规划

通过修改经典的序列二次规划 (SQP) 算法，开发了一种利用许多设计问题中存在的对数凸结构的新方法。改进后的对数空间序列二次规划 (LSQP) 算法继承了几何规划和符号规划等对数凸方法所表现出的一些计算效率，但保留了 SQP 中黑盒分析方法的自然集成。因此，无需对实际设计问题中普遍存在的现有黑盒分析方法进行侵入性修改，即可实现显着的计算节省。在此处考虑的情况下，与 SQP 相比，LSQP 算法的迭代次数减少了 40-70%。