Optimization of Structures Using Improved Genetic Algorithms for Discrete Variables

Abstract:

Genetic algorithms (GA) have been shown to be very effective optimization tools for a number of engineering problems. Genetic algorithms which are based upon the principles of Darwinian evolution explores the region of the whole solution space and can obtain the golbal optimum. This paper introduces the standard GA and the forward-and-back search algorithms (FBSA) and demonstrates the use of improved genetic algorithms (IGA) for structure optimization of discrete variables. The mathematical model of structural optimization is derived. A 10-bar benchmark example is studied, the result shows that IGA, as an efficient method,can be applied to structure optimization of discrete variables.

• Periodical: Advanced Materials Research (Volumes 163-167)
• Pages: 2437-2440
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.163-167.2437
• Online since: December 2010
• Authors: Yuan Tian, Qing Xuan Shi, Chao Yan Zhu
• Keywords: Discrete Variable, Genetic Algorithm (GA), Improved Genetic Algorithm (IGA), Structure Optimization

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