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A hybrid genetic based optimization procedure for aircraft conceptual analysis

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Abstract

The problem to define a methodology for the analysis of aircraft performances, in the phase of conceptual design, is addressed. The proposed approach is based on a numerical optimization procedure where a scalar objective function, the take-off weight, is minimized. Deterministic and stochastic approaches as well as hybridizations between these two search techniques are considered. More precisely, we consider two-stage strategies where the optimum localization is performed by a genetic algorithm, while a gradient-based method is used to terminate the optimization process. Also, another type of hybridization strategy is investigated where a partially converged gradient-based method is incorporated in the genetic algorithm as a new operator. A detailed discussion is made and various different solutions are critically compared.

The proposed methodology is consistent and capable of giving fundamental information to the designer for further investigating towards the directions identified by the procedure.

A basic example is described, and the use of the methodology to establish the effects of different geometrical and technological parameters is discussed.

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Authors and Affiliations

  1. Department of Aerospace Engineering, University of Pisa, Via Caruso, 56122, PISA, Italy

    Giovanni Lombardi & Giovanni Mengali

  2. Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, 56126, PISA, Italy

    Francois Beux

Authors
  1. Giovanni Lombardi
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  2. Giovanni Mengali
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  3. Francois Beux
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Correspondence to Giovanni Lombardi.

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Lombardi, G., Mengali, G. & Beux, F. A hybrid genetic based optimization procedure for aircraft conceptual analysis. Optim Eng 7, 151–171 (2006). https://doi.org/10.1007/s11081-006-6837-1

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  • DOI: https://doi.org/10.1007/s11081-006-6837-1

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