2010Advanced materials researchOpen access

The Truss Structural Optimization Design Based on Improved Hybrid Genetic Algorithm

Feng Guo Jiang, Zhen Qing Wang

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Abstract

Genetic arithmetic operators in genetic algorithm be improved , and a hybrid genetic algorithm of a gradient algorithm combining with the genetic algorithm be given against to the defects such as premature,slow on convergence rate,weak in the ability of local search ,all these appeared on the progress of genetic algorithm's iteration. Analysis result indicate that not only strong on the local search capacity of gradient algorithm be exhibited but also strong on the general search capacity of genetic algorithm be combined based on the hybrid genetic algorithm ,which make phenomenon of premature avoid, and the rate of convergence be improved greatly. Concrete calculated example indicated that the hybrid genetic algorithm is an effective structural optimization method.

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What this paper is about

Genetic arithmetic operators in genetic algorithm be improved , and a hybrid genetic algorithm of a gradient algorithm combining with the genetic algorithm be given against to the defects such as premature,slow on convergence rate,weak in the ability of local search ,all these appeared on the progress of genetic algorithm's iteration. Analysis result indicate that not only strong on the local search capacity of gradient algorithm be exhibited but also strong on the general search capacity of genetic algorithm be combined based on the hybrid genetic algorithm ,which make phenomenon of premature avoid, and the rate of convergence be improved greatly. Concrete calculated example indicated that the hybrid genetic algorithm is an effective structural optimization method.

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Available abstract

Genetic arithmetic operators in genetic algorithm be improved , and a hybrid genetic algorithm of a gradient algorithm combining with the genetic algorithm be given against to the defects such as premature,slow on convergence rate,weak in the ability of local search ,all these appeared on the progress of genetic algorithm's iteration. Analysis result indicate that not only strong on the local search capacity of gradient algorithm be exhibited but also strong on the general search capacity of genetic algorithm be combined based on the hybrid genetic algorithm ,which make phenomenon of premature avoid, and the rate of convergence be improved greatly. Concrete calculated example indicated that the hybrid genetic algorithm is an effective structural optimization method.

Key concepts: Genetic algorithm, Truss, Population-based incremental learning, Meta-optimization, Algorithm, Mathematical optimization, Convergence (economics), Rate of convergence

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