The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

Abstract:

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

• Periodical: Applied Mechanics and Materials (Volume 721)
• Pages: 464-467
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.721.464
• Online since: December 2014
• Authors: Tao Fu*, Qin Zhong Gong, Da Zhen Wang
• Keywords: HPSO Algorithm, Machine Tool Spindle, Robust Design, Uncertainty Analysis

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