In this paper, the combined optimization algorithm (immune-genetic algorithm) is proposed for multioptimization problems by introducing the capability of the immune system to the genetic algorithm. The optimizing ability of the proposed combined algorithm is identified by comparing the result of optimization with sharing genetic algorithm for the two-dimensional multipeak function. Also the combined algorithm is applied to minimize the total weight of the shaft and the transmitted forces at the bearings. The results show that the combined algorithm can reduce both the weights of the shaft and the transmitted forces at the bearing with dynamic constraints.
Multiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm
Contributed by the Structures & Dynamics Division of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received by the S&D Division, Jan. 1999; final revision received by the ASME Headquarters, Sept. 28, 1999. Editor: H. D. Nelson.
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Choi, B., and Yang, B. (September 28, 1999). "Multiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm ." ASME. J. Eng. Gas Turbines Power. January 2001; 123(1): 78–81. https://doi.org/10.1115/1.1338952
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