Utilizing object-oriented design to build advanced optimization strategies with generic implementation

the benefits of applying optimization to computational models are well known, but their range of widespread application to date has been limited. This effort attempts to extend the disciplinary areas to which optimization algorithms may be readily applied through the development and application of advanced optimization strategies capable of handling the computational difficulties associated with complex simulation codes. Towards this goal, a flexible software framework is under continued development for the application of optimization techniques to broad classes of engineering applications, including those with high computational expense and nonsmooth, nonconvex design space features. Object-oriented software design with C++ has been employed as a tool in providing a flexible, extensible, and robust multidisciplinary toolkit with computationally intensive simulations. In this paper, demonstrations of advanced optimization strategies using the software are presented in the hybridization and parallel processing research areas. Performance of the advanced strategies is compared with a benchmark nonlinear programming optimization