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.

翻译：通过修改古典的 " 序列二次曲线编程(SQP) " 算法,形成了一种利用许多设计问题中存在的对数曲线结构的新办法。经修改的算法,即 " 逻辑空间二次曲线编程(LSQP) ",继承了诸如几何编程和信号程序等对数曲线方法所显示的一些计算效率,但保留了SQP黑盒分析方法的自然结合。因此,在计算上节省了大量费用,而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。在此审议的案件中,LSQP算法显示,与SQP相比,迭代数减少了40-70%。