Optimization for aerospace conceptual design through the use of genetic algorithms

Abstract

Using a genetic algorithm (GA) as a non-calculus-based global search method allows optimization-like techniques to be applied in the conceptual phase of design, which traditionally has been dominated by qualitative or subjective decision making. Features of the GA provide several advantages for conceptual design including: the ability to combine discrete, integer and continuous variables, the population-based search, no requirement for an initial design, and the ability to address non-convex, multimodal and discontinuous functions. Examples of applications to aerospace system conceptual design include aerospace vehicle design and satellite constellation design. A multiobjective design approach using the GA is also discussed.