Abstract
The theory and methodology of finding the best possible solution to a broad range of optimization problems has been of interest since the beginnings of modern operations research. The key theoretical results regarding important model types and algorithmic frameworks have been followed by optimization software implementations that are used to handle a large and still growing variety of applications. Our discussion is focused on the practice of nonlinear—specifically including also global and mixed integer optimization, in the context of space engineering applications. We review some of the prominent solution approaches, model development tools, and software implementations of optimization (solver) engines and then relate our discussion to selected applications in space engineering. The review portion of this work cites contributions by our coauthors to the present volume (Fasano and Pintér, Modeling and Optimization in Space Engineering, Springer Science + Business Media, New York, 2012) while also drawing on an extensive list of other sources.
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