• DocumentCode
    618208
  • Title

    Application of the multi-objective Alliance Algorithm to a benchmark aerodynamic optimization problem

  • Author

    Lattarulo, Valerio ; Kipouros, Timoleon ; Parks, Geoffrey T.

  • Author_Institution
    Dept. of Eng., Univ. of Cambridge, Cambridge, UK
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    3182
  • Lastpage
    3189
  • Abstract
    This paper introduces a new version of the multiobjective Alliance Algorithm (MOAA) applied to the optimization of the NACA 0012 airfoil section, for minimization of drag and maximization of lift coefficients, based on eight section shape parameters. Two software packages are used: XFoil which evaluates each new candidate airfoil section in terms of its aerodynamic efficiency, and a Free-Form Deformation tool to manage the section geometry modifications. Two versions of the problem are formulated with different design variable bounds. The performance of this approach is compared, using two indicators and a statistical test, with that obtained using NSGA-II and multi-objective Tabu Search (MOTS) to guide the optimization. The results show that the MOAA outperforms MOTS and obtains comparable results with NSGA-II on the first problem, while in the other case NSGA-II is not able to find feasible solutions and the MOAA is able to outperform MOTS.
  • Keywords
    aerodynamics; drag; genetic algorithms; mechanical engineering computing; search problems; software packages; statistical testing; MOAA; MOTS; NACA 0012 airfoil section; XFoil; aerodynamic efficiency; benchmark aerodynamic optimization problem; design variable bounds; drag minimization; free-form deformation tool; lift coefficient maximization; multiobjective alliance algorithm; multiobjective tabu search; section geometry modification management; section shape parameters; software packages; statistical test; Aerodynamics; Algorithm design and analysis; Automotive components; Geometry; Linear programming; Optimization; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557959
  • Filename
    6557959