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Cloud Service Optimization Method Based on Dynamic Artificial Ant-Bee Colony Algorithm in Agricultural Equipment Manufacturing.

Authors :
Zhou, Kai
Wen, Yongzhao
Wu, Wanying
Ni, Zhiyong
Jin, Tianguo
Long, Xiaojun
Source :
Mathematical Problems in Engineering. 10/28/2020, p1-11. 11p.
Publication Year :
2020

Abstract

In view of the miniaturization and decentralization characteristics of agricultural equipment factories in China, agricultural equipment manufacturing is well suited to the cloud manufacturing model, but there is no specific research on cloud services optimization for it. To fill the research gap, a cloud service optimization method is proposed in this paper. For the optimization model, the dynamic coefficient strategy and the reliability feedback update strategy are added to the mathematical model to strengthen the applicability of farming season. As optimization algorithm, a dynamic artificial ant-bee colony algorithm (DAABA) based on artificial ant colony algorithm and bee colony algorithm is presented. The optimal fusion evaluation strategy is used to save optimization time by reducing the useless iteration, and the iterative adjustment threshold strategy is adopted to improve the accuracy of cloud service by increasing the size of bee colony. Finally, the performance of DAABA is verified to be more superior by comparing with other algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1024123X
Database :
Academic Search Index
Journal :
Mathematical Problems in Engineering
Publication Type :
Academic Journal
Accession number :
146678608
Full Text :
https://doi.org/10.1155/2020/9134695