• DocumentCode
    1445870
  • Title

    Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace Engineering

  • Author

    Arias-Monta, Alfredo ; Coello, Carlos A Coello ; Mezura-Montes, Efrén

  • Author_Institution
    Dept. of Comput. Sci., Inst. Politec. Nac., Mexico City, Mexico
  • Volume
    16
  • Issue
    5
  • fYear
    2012
  • Firstpage
    662
  • Lastpage
    694
  • Abstract
    Nowadays, the solution of multiobjective optimization problems in aeronautical and aerospace engineering has become a standard practice. These two fields offer highly complex search spaces with different sources of difficulty, which are amenable to the use of alternative search techniques such as metaheuristics, since they require little domain information to operate. From the several metaheuristics available, multiobjective evolutionary algorithms (MOEAs) have become particularly popular, mainly because of their availability, ease of use, and flexibility. This paper presents a taxonomy and a comprehensive review of applications of MOEAs in aeronautical and aerospace design problems. The review includes both the characteristics of the specific MOEA adopted in each case, as well as the features of the problems being solved with them. The advantages and disadvantages of each type of approach are also briefly addressed. We also provide a set of general guidelines for using and designing MOEAs for aeronautical and aerospace engineering problems. In the final part of the paper, we provide some potential paths for future research, which we consider promising within this area.
  • Keywords
    aerospace engineering; design engineering; evolutionary computation; optimisation; search problems; MOEA; aeronautical engineering design problems; aerospace engineering design problem; metaheuristics; multiobjective evolutionary algorithms; multiobjective optimization problems; search spaces; Aerospace engineering; Analytical models; Computational fluid dynamics; Computational modeling; Evolutionary computation; Optimization; Vectors; Artificial intelligence; evolutionary algorithms; multiobjective optimization; optimization methods;
  • fLanguage
    English
  • Journal_Title
    Evolutionary Computation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-778X
  • Type

    jour

  • DOI
    10.1109/TEVC.2011.2169968
  • Filename
    6151094