MATEC Web Conf.
Volume 173, 20182018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|Number of page(s)||5|
|Section||Digital Signal and Image Processing|
|Published online||19 June 2018|
A Parameter Adaptive Genetic Algorithm Based Service Compositions
School of Computer Science, Xi’an ShiYou University, 710065, Shaanxi, China
* Corresponding author: email@example.com
How to select and combine many services with similar functions reasonably and efficiently to provide users with better service is the main challenge in the service composition problem. This is thorny when the number of the candidate Services is huge. Recently, researches transform the service compositions problem as a multi-objective optimizing task, and then the genetic algorithm is commonly used to tackle this issue. However, the fixed crossover probability and mutation probability settings in genetic algorithm usually result to it falls into a local optimal. To improve the performance of the genetic algorithm in the service composition task, this paper proposes an adaptive parameter adjust strategy, which can adjust the crossover probability and mutation probability automatically. The experiment result shows our method has greatly improved the maximum fitness of the final solutions of traditional genetic algorithm.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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