Development of a multiple sampling extension for a mixed integer efficient global optimization (amiego) mixed integer nonlinear programming algorithm. A recently published algorithm for mixed…

This federal contract award to the National Institute of Aerospace Associates (NIA), a non-profit research institute, was issued by the National Aeronautics and Space Administration's (NASA) Langley Research Center. The $48,290.37 cost-plus-fixed-fee delivery order is for the development of a mixed integer efficient global optimization (AMIEGO) algorithm within NASA's OpenMDAO framework. This algorithm can benefit from gradient-based optimization with analytic derivatives and has applications for solving mixed integer nonlinear programming problems, including a large-scale wing topology optimization problem of interest to NASA's Aeronautics Research Mission Directorate. The contract does not have a set-aside designation. Purdue University Global is listed as a subcontractor to implement the AMIEGO algorithm and demonstrate it on the wing optimization problem.

Development of a multiple sampling extension for a mixed integer efficient global optimization (amiego) mixed integer nonlinear programming algorithm. A recently published algorithm for mixed integer nonlinear programming, a mixed integer efficient global optimization (amiego), has significantly advanced the state of the art for solving optimization problems with both integer and continuous design variables. This algorithm can benefit greatly from exploiting gradient based optimization with analytic derivatives for its inner optimization routine. NASA s openmdao framework specializes in gradient based optimization with analytic derivatives, which makes IT a natural place to implement the newly created amiego algorithm. There are a number of interesting mixed integer nonlinear programming problems that are of interest to NASA aeronautics research mission directorate s (armd) transformational tools and technologies (TTT) project, including the solution to a large scale wing topology optimization optimization problem. The goal of this work is to implement the amiego algorithm within openmdao, using a multiple sampling based infill criterion and then to demonstrate the algorithm on the solution of the wing optimization problem.