Multi-Objective Optimal Design of Rotor-Bearing Systems under Dynamic Behavior Constraints Using a Hybrid Genetic Algorithm

應用複合基因遺傳演算法於轉子軸承系統在動態行為限制下之多目標最佳化設計

蕭庭郎(Ting-Nung Shiau) ； 康仲豪(Chung-Hao Kang) ； 劉徳騏(De-Shin Liu)

《中國機械工程學刊》 29卷3期 (2008/06) Pp. 187-194

https://doi.org/10.29979/JCSME.200806.0001

摘要

本篇論文主要提出一複合之最佳化設計程序，其結合傳統最佳化方法與遺傳演算法，並在轉子軸承系統的最佳化設計問題上做驗證。以往在進行最佳化設計時，容易面臨如何選擇起始設計值的難題；本文所提出之方法，將利用遺傳演算法廣域搜尋之優點來尋得較佳之起始設計參數，再引入傳統最佳化方法來進行設計。根據數值結果顯示，藉由此複合之方法，不論針對單目標亦或是多目標最佳化設計所得到之結果，均較單利用傳統最佳化方法為佳。

並列摘要

A new hybrid optimization procedure of rotorbearing systems, which combines the genetic algorithm (GA) with traditional optimization methods, is presented in this paper. Most traditional optimization methods applied in engineering design require a better set of initial values for the design variables, and then converge rapidly to generate good results. In the first step of the procedure, a GA is applied to provide a set of initial design variables, thereby avoiding the trial process; thereafter, traditional algorithms are employed to determine the optimum results. This hybrid algorithm, which can be termed a hybrid genetic algorithm (HGA), is more effective than the traditional ones. The capacity of the HGA is demonstrated by the optimization of rotor-bearing systems under dynamic behavior constraints. The optimization involves minimizing, either individually or simultaneously, the shaft weight and the transmitted forces at the bearings. The results show that an HGA can identify more effectively better initial design variables. Moreover, it can identify superior optimized results; for example, reducing both the shaft weight and transmitted forces of the bearing for rotor-bearing systems under critical speed constraints.

並列關鍵字

hybrid optimization procedure ； genetic algorithm ； multi-objective ； single-objective ； rotorbearing system ； dynamic behavior constraints