  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.
