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.

Issue Section:
Gas Turbines: Structures and Dynamics
Keywords:
design engineering, design aids, genetic algorithms, constraint theory, rotors, machine bearings, weight control, force control
Topics:
Algorithms, Bearings, Design, Genetic algorithms, Optimization, Rotors, Weight (Mass)
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Copyright © 2001
 by ASME
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