Conceptual Aircraft Design Based on a Multiconstraint Genetic Optimizer

Introduction I N the last years genetic algorithms (GAs) have received much attention as a powerful design tool in many areas of aerospace engineering. These probabilistic-typemethods, based on the principle of the natural evolution, have shown their effectiveness and robustness in a wide range of optimizationproblems. i 5 Compared with classical deterministic approaches, GAs’ superior effectiveness in performing optimization tasks is mainly from some speciŽ c features such as the capability to handle simultaneously continuous integer and discrete design variables, a parallel-like searching method leadingto a greatereffectivenessin Ž ndingglobalminimum within the design space. Moreover, as genetic-type optimization is guided only by a function of merit (or Ž tness) value, no mathematical informationon the objective function is required.Therefore function discontinuitiescan be easily managed. In this Note an application in the Ž eld of aircraft conceptual design is described. A genetic optimizer has been coupled with a sizing code to deŽ ne a short/medium range preliminary aircraft conŽ guration,powered by turbofan engines, fully compliant with given requirements and allowingminimumdirect operatingcost. Parametric formulas6 i 8 have been used for aerodynamics, weights, and low-speed performance calculation.Rationale for GA application in conceptualdesignwith reference to selection and sizing is well presented in Ref. 9. Other relevantexamplesof geneticapproachin aircraftdesignare reported in Refs. 10–13.