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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 278-280Performance Test Functions of Genetic Algorithm

Performance Test Functions of Genetic Algorithm

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Abstract:

Due to the disadvantages of genetic algorithm such as the weaker ability for local search, premature convergence, random walk and problems related, and so on , the design and improvement of the algorithm is an important research direction of genetic algorithm. And evaluating the performance of algorithm systematically and scientifically is the key to test algorithm whether good or bad .The common method used to evaluate algorithm is test function, however, the existing literature on the optimization algorithm has different methods to evaluate the performance of algorithm, and there is no uniform test criteria. As for those questions above, This paper studies test functions of genetic algorithm, and analyses characteristics of the main test functions, which can be used as the basis of selection algorithm test functions.

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Periodical:

Applied Mechanics and Materials (Volumes 278-280)

Pages:

1334-1337

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.278-280.1334

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Online since:

January 2013

Authors:

Wen Xia Yun, Yong Jie Ma, Ying Chen

Keywords:

Constrained Optimization, Genetic Algorithm (GA), Multimodal Optimization, Performance Metrics, Test Functions

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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