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Construction of Integral Objective Function/Fitness Function of Multi-Objective/Multi-Disciplinary Optimization

Z. Q. Zhu1, Z. Liu1, X. L. Wang1, R. X. Yu1
Institute of Fluid Mechanics, Beijing University of Aeronautics and Astronautics, Beijing 100083

Computer Modeling in Engineering & Sciences 2004, 6(6), 567-576. https://doi.org/10.3970/cmes.2004.006.567

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.

Keywords

multiobjective/multidisciplinary optimization, Euler equations, Maxwell equations, genetic algorithms

Cite This Article

Zhu, Z. Q., Liu, Z., Wang, X. L., Yu, R. X. (2004). Construction of Integral Objective Function/Fitness Function of Multi-Objective/Multi-Disciplinary Optimization. CMES-Computer Modeling in Engineering & Sciences, 6(6), 567–576.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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