Research and implementation on genetic algorithms for graph fitness optimization

Authors:
Jin Min;Wang Qin;Xi Lifeng
Affiliations:
Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, China
Venue:
WSEAS TRANSACTIONS on SYSTEMS
Year:
2008

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Abstract

Graph fitness optimization is a difficult problem in data fitness. Genetic algorithms(GAs), which can yield accurate results if they start with suitable parameters, have been used to solve difficult problems with objective functions which usually are multi-modal, discontinuous, and nondifferentiable. In this paper, we design a genetic algorithm (GA) to optimize effect on self-affine fractal interpolation function (AFIF) and give result. The software was tested on realistic graphs. The validation and effectiveness of the method to be able to find the optimal fractal function are presented and demonstrated.