Privacy preservation of cloud data in business application enabled by multi-objective red deer-bird swarm algorithm

2021 ◽  
pp. 107748
Author(s):  
Balashunmugaraja B. ◽  
T.R. Ganeshbabu
2018 ◽  
Vol 79 (21-22) ◽  
pp. 14319-14339 ◽  
Author(s):  
Dongmei Wu ◽  
Chi-Man Pun ◽  
Bin Xu ◽  
Hao Gao ◽  
Zhenghua Wu

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 36382-36398
Author(s):  
Essam H. Houssein ◽  
Mohammed M. Ahmed ◽  
Mohamed Abd Elaziz ◽  
Ahmed A. Ewees ◽  
Rania M. Ghoniem

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 36078-36086
Author(s):  
Chengchang Zhang ◽  
Sa Yu ◽  
Guojun Li ◽  
Yu Xu

Author(s):  
Wei Guo ◽  
Pingyu Jiang

For adapting the socialization, individuation and servitization in manufacturing industry, a new manufacturing paradigm called social manufacturing has received a lot of attention. Social manufacturing can be seen as a network that enterprises with socialized resources self-organized into communities that provide personalized machining and service capabilities to customers. Since a community of social manufacturing has multiple enterprises and emphasizes on the importance of service, manufacturing service order allocation must be studied from the new perspective considering objectives on service cost and quality of service. The manufacturing service order allocation can be seen as a one-to-many game model with multi-objective. In this article, a Stackelberg game model is proposed to tackle the manufacturing service order allocation problem with considering the payoffs on cost and quality of service. Since this Stackelberg game can be mapped to a multi-objective bi-level programming, a modified multi-objective hierarchical Bird Swarm Algorithm is used to find the Nash equilibrium of the game. Finally, a case from a professional printing firm is analyzed to validate the proposed methodology and model. The objective of this research is to find the Nash equilibrium on the manufacturing service order allocation and provide strategies guidance for customer and small- and medium-sized enterprises with optimal service cost and lead time. According to the game process and Nash equilibrium, some rules are revealed, and they are useful for guiding practical production.


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