Peer-to-Peer Networking and Applications

, Volume 11, Issue 5, pp 1115–1128 | Cite as

Self-adaptive bat algorithm for large scale cloud manufacturing service composition

  • Bin XuEmail author
  • Jin Qi
  • Xiaoxuan Hu
  • Kwong-Sak Leung
  • Yanfei Sun
  • Yu Xue
Part of the following topical collections:
  1. Special Issue on Big Data Networking


In order to cope with the current economic situation and the trend of global manufacturing, Cloud Manufacturing Mode (CMM) is proposed as a new manufacturing model recently. Massive manufacturing capabilities and resources are provided as manufacturing services in CMM. How to select the appropriate services optimally to complete the manufacturing task is the Manufacturing Service Composition (MSC) problem, which is a key factor in the CMM. Since MSC problem is NP hard, solving large scale MSC problems using traditional methods may be highly unsatisfactory. To overcome this shortcoming, this paper investigates the MSC problem firstly. Then, a Self-Adaptive Bat Algorithm (SABA) is proposed to tackle the MSC problem. In SABA, three different behaviors based on a self-adaptive learning framework, two novel resetting mechanisms including Local and Global resetting are designed respectively to improve the exploration and exploitation abilities of the algorithm for various MSC problems. Finally, the performance of the different flying behaviors and resetting mechanisms of SABA are investigated. The statistical analyses of the experimental results show that the proposed algorithm significantly outperforms PSO, DE and GL25.


Manufacturing service composition Self-adaptive learning Bat algorithm Dual resetting 



This paper was supported by Natural Science Foundation of China (61572262), Natural Science Foundation of Jiangsu Province of China (No. BK20160910, BK20141427), Natural science fund for colleges and universities in Jiangsu Province (No. 16KJB520034), NUPTSF (Grant Nos. NY213047, NY213050, NY214102, NY214098), A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.School of Internet of ThingsNanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.School of AutomationNanjing University of Posts and TelecommunicationsNanjingChina
  3. 3.Chinese University of Hong KongShatinHong Kong
  4. 4.School of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingChina

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