Construction of integral objective function/fitness function of multi-objective/multi-disciplinary optimization

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

To extend an available mono-objective optimization method to multi-objective/multi-disciplinary optimization, the construction of a suitable integral objective function (in gradient based deterministic method-DM) or fitness function (in genetic algorithm-GA) is important. An auto-adjusting weighted object optimization (AWO) method in DM is suggested to improve the available weighted sum method (linear combined weighted object optimizationLWO method). Two formulae of fitness function in GA are suggested for two kinds of design problems. Flow field solution is obtained by solving Euler equations. Electromagnetic field solution is obtained by solving Maxwell equations. Bi-disciplinary optimization computation is carried out by coupling these two solutions with a nonlinear optimization method. Numerical results show that the needed Pareto solutions can be effectively obtained by using these suggested methods to meet the original design requirements.

Detaljer

Författare
Externa organisationer
  • Beihang University
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Maskinteknik

Nyckelord

Originalspråkengelska
Sidor (från-till)567-576
Antal sidor10
TidskriftCMES - Computer Modeling in Engineering and Sciences
Volym6
Utgivningsnummer6
StatusPublished - 2004 dec 1
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa