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

Z. Q. Zhu, Z. Liu, X. L. Wang, R. X. Yu

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)567-576
Number of pages10
JournalCMES - Computer Modeling in Engineering and Sciences
Volume6
Issue number6
Publication statusPublished - 2004 Dec 1
Externally publishedYes

Subject classification (UKÄ)

  • Mechanical Engineering

Free keywords

  • Euler equations
  • Genetic algorithms
  • Maxwell equations
  • Multiobjective/multidisciplinary optimization

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