A robust service composition and optimal selection method for cloud manufacturing

References

• Arora, N., X. Dreze, A. Ghose, J. D. Hess, R. Iyengar,B. Jing, Y. Joshi, et al. 2008. “Putting one-to-one Marketing to Work: Personalization, Customization, and Choice.” Marketing Letters 19 (3-4): 305–321.
   Web of Science ®Google Scholar
• Bouzary, Hamed, and F. Frank Chen. 2019. “A Hybrid Grey Wolf Optimizer Algorithm with Evolutionary Operators for Optimal QoS-Aware Service Composition and Optimal Selection in Cloud Manufacturing.” International Journal of Advanced Manufacturing Technology 101: 2771–2784.
   Web of Science ®Google Scholar
• Chen, Fuzan, Runliang Dou, Minqiang Li, and Harris Wu. 2016. “A Flexible QoS-Aware Web Service Composition Method by Multi-Objective Optimization in Cloud Manufacturing.” Computers & Industrial Engineering 99: 423–431.
   Web of Science ®Google Scholar
• Chen, Shengkai, Shuiliang Fang, and Renzhong Tang. 2019. “A Reinforcement Learning Based Approach for Multi-Projects Scheduling in Cloud Manufacturing.” International Journal of Production Research 57 (10): 3080–3098.
   Web of Science ®Google Scholar
• Cheng, Zhen, Dechen Zhan, Xibin Zhao, and Hai Wan. 2014. “Multitask Oriented Virtual Resource Integration and Optimal Scheduling in Cloud Manufacturing.” Journal of Applied Mathematics 2014: 1–9. Article ID 369350.
   Google Scholar
• Elkins, Debra A., Ningjian Huang, and Jeffrey M. Alden. 2004. “Agile Manufacturing Systems in the Automotive Industry.” International Journal of Production Economics 91 (3): 201–214.
   Web of Science ®Google Scholar
• Fazeli, Mohammad Moein, Yaghoub Farjami, and Mohsen Nickray. 2019. “An Ensemble Optimisation Approach to Service Composition in Cloud Manufacturing.” International Journal of Computer Integrated Manufacturing 32 (1): 83–91.
   Web of Science ®Google Scholar
• Gaidhane, Prashant J., and Madhav J. Nigam. 2018. “A Hybrid Grey Wolf Optimizer and Artificial bee Colony Algorithm for Enhancing the Performance of Complex Systems.” Journal of Computational Science 27: 284–302.
   Web of Science ®Google Scholar
• Gao, B., S. L. Wang, L. Kang, X. Shu, and X. X. Yang. 2018. “Diagnosis and Handling of Exception in Cloud Manufacturing.” Prognostics and System Health Management Conference 866–870.
   Google Scholar
• Ghomi, Einollah Jafarnejad, Amir Masoud Rahmani, and Nooruldeen Nasih Qader. 2019. “Service Load Balancing, Task Scheduling and Transportation Optimisation in Cloud Manufacturing by Applying Queuing System.” Enterprise Information Systems 13 (6): 865–894.
   Web of Science ®Google Scholar
• Guopu, Zhu, and Kwong Sam. 2010. “Gbest-guided Artificial bee Colony Algorithm for Numerical Function Optimization.” Applied Mathematics and Computation 217: 3166–3173.
   Web of Science ®Google Scholar
• Heidari, Ali Asghar, Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah, Majdi Mafarja, and Huiling Chen. 2019. “Harris Hawks Optimization: Algorithm and Applications.” Future Generation Computer Systems 97: 849–872.
   Web of Science ®Google Scholar
• Hu, Yanjuan, Feifan Zhu, Lin Zhang, Yongkui Lui, and Zhanli Wang. 2019. “Scheduling of Manufacturers Based on Chaos Optimization Algorithm in Cloud Manufacturing.” Robotics and Computer Integrated Manufacturing 58: 13–20.
   Web of Science ®Google Scholar
• Huang, Biqing, Chenghai Li, and Fei Tao. 2014. “A Chaos Control Optimal Algorithm for QoS-Based Service Composition Selection in Cloud Manufacturing System.” Enterprise Information Systems 8 (4): 445–463.
   Web of Science ®Google Scholar
• Jamili, Amin. 2016. “Robust job Shop Scheduling Problem: Mathematical Models, Exact and Heuristic Algorithms.” Expert Systems With Applications 55: 341–350.
   Web of Science ®Google Scholar
• Jiajun, Zhou, Yao Xifan, Lin Yingzi, Chan Felix T.S., and Li Yun. 2018. “An Adaptive Multi-Population Differential Artificial bee Colony Algorithm for Many-Objective Service Composition in Cloud Manufacturing.” Information Sciences 456: 50–82.
   Web of Science ®Google Scholar
• Jin, Hong, Xifan Yao, and Yong Chen. 2017. “Correlation-aware QoS Modeling and Manufacturing Cloud Service Composition.” Journal of Intelligent Manufacturing 28: 1947–1960.
   Web of Science ®Google Scholar
• Jun, Luo, and Wang Qian. 2014. “A Method for Axis Straightness Error Valuation Based on Improved Artificial bee Colony Algorithm.” International Journal of Advanced Manufacturing Technology 71: 1501–1509.
   Web of Science ®Google Scholar
• Karaboga, D., and B. Basturk. 2008. “On the Performance of Artificial bee Colony (ABC) Algorithm.” Applied Soft Computing 8: 687–697.
   Web of Science ®Google Scholar
• Lartigau, Jorick, Xiaofei Xu, Lanshun Nie, and Dechen Zhan. 2015. “Cloud Manufacturing Service Composition Based on QoS with geo-Perspective Transportation Using an Improved Artificial Bee Colony Optimisation Algorithm.” International Journal of Production Research 53: 4380–4404.
   Web of Science ®Google Scholar
• Lei, D. 2012. “Minimizing Makespan for Scheduling Stochastic Job Shop with Random Breakdown.” Appl. Math. Comput 218: 11851–11858.
   Web of Science ®Google Scholar
• Li, Feng, T. W. Liao, and Lin Zhang. 2019. “Two-level Multi-Task Scheduling in a Cloud Manufacturing Environment.” Robotics and Computer Integrated Manufacturing 56: 127–139.
   Web of Science ®Google Scholar
• Li, Yongxiang, Xifan Yao, and Jifeng Zhou. 2016. “Multi-objective Optimization of Cloud Manufacturing Service Composition with Cloud-Entropy Enhanced Genetic Algo-rithm.” Journal of Mechanical Engineering 62 (10): 577–590.
   Web of Science ®Google Scholar
• Li, B. H., L. Zhang, S. L. Wang, F. Tao, J. W. Cao, X. D. Jiang, X. Song, and X. D. Chai. 2010. “Cloud Manufacturing: A New Service-Oriented Networked Manufacturing Model.” Computer Integrated Manufacturing Systems 16 (1): 1–16.
   Google Scholar
• Liu, Jian, and Youling Chen. 2019. “A Personalized Clustering-Based and Reliable Trust-Aware QoS Prediction Approach for Cloud Service Recommendation in Cloud Manufacturing.” Knowledge-Based Systems 174: 43–56.
   Web of Science ®Google Scholar
• Liu, Weining, Bo Liu, Dihua Sun, Yiming Li, and Gang Ma. 2013. “Study on Multi-Task Oriented Services Composition and Optimisation with the Multi Composition for Each Task Pattern in Cloud Manufacturing Systems.” International Journal of Computer Integrated Manufacturing 26 (8): 786–805.
   Web of Science ®Google Scholar
• Liu, Zhi-Zhong, Cheng Song, Dian-Hui Chu, Zhan-Wei Hou, and Wei-Ping Peng. 2017. “An Approach for Multipath Cloud Manufacturing Services Dynamic Composition.” International Journal of Intelligent Systems 32: 371–393.
   Web of Science ®Google Scholar
• Liu, Bo, and Zili Zhang. 2017. “QoS-aware Service Composition for Cloud Manufacturing Based on the Optimal Construction of Synergistic Elementary Service Groups.” The International Journal of Advanced Manufacturing Technology 88: 2757–2771.
   Web of Science ®Google Scholar
• Magnusson, M., and M. Pasche. 2014. “A Contingency-Based Approach to the use of Product Platforms and Modules in new Product Development.” Journal of Product Innovation Management 31 (3): 434–450.
   Web of Science ®Google Scholar
• Mirjalili, Seyedali, Seyed Mohammad Mirjalili, and Andrew Lewis. 2014. “Grey Wolf Optimizer.” Advances in Engineering Software 69: 46–61.
   Web of Science ®Google Scholar
• Nouiri, M., A. Bekrar, A. Jemai, D. Trentesaux, A. C. Ammari, and S. Niar. 2017. “Two Stage Particle Swarm Optimization to Solve the Flexible job Shop Predictive Scheduling Problem Considering Possible Machine Breakdowns.” Computers & Industrial Engineering 112: 595–606.
   Web of Science ®Google Scholar
• Song, T., H. Liu, C. Wei, and C. Zhang. 2014. “Common Engines of Cloud Manufacturing Service Platform for SMES.” The International Journal of Advanced Manufacturing Technology 73 (1-4): 557–569.
   Web of Science ®Google Scholar
• Tao, Fei, Yuanjun LaiLi, Lida Xu, and Lin Zhang. 2013. “FC-PACO-RM: A Parallel Method for Service Composition Optimal-Selection in Cloud Manufacturing System.” IEEE Transactions on Industrial Informatics 9 (4): 2023–2033.
   Web of Science ®Google Scholar
• Tao, Fei, Dongming Zhao, Yefa Hu, and Zude Zhou. 2008. “Resource Service Composition and its Optimal-Selection Based on Particle Swarm Optimization in Manufacturing Grid System.” IEEE Transactions on Industrial Informatics 4 (4): 315–327.
   Web of Science ®Google Scholar
• Tao, F., D. Zhao, Y. Hu, and Z. Zhou. 2010. “Correlation-aware Resource Service Composition and Optimal-Selection in Manufacturing Grid.” European Journal of Operational Research 201 (1): 129–143.
   Web of Science ®Google Scholar
• Ulieru, Mihaela, and Rainer Unland. 2004. “Enabling Technologies for the Creation and Restructuring Process of Emergent Enterprise Alliances.” International Journal of Information Technology & Decision Making 3 (1): 33–60.
   Web of Science ®Google Scholar
• Wei, L., Q. Y. Zhao, and H. P. Shu. 2012. “Adaptive Adjustment of Composite Cloud Service Based on QoS for Cloud Manufacturing Environment.” Journal of Lanzhou University (Natural Sciences) 48 (4): 98–104.
   Google Scholar
• Wu, D., M. J. Greer, D. W. Rosen, and D. Schaefer. 2013. “Cloud Manufacturing: Strategic Vision and State of-the-art.” Journal of Manufacturing Systems 32 (4): 564–579.
   Web of Science ®Google Scholar
• Wu, Z., S. Sun, and S. Xiao. 2018. “Risk Measure of job Shop Scheduling with Random Machine Breakdowns.” Computers & Operations Research 99: 1–12.
   Web of Science ®Google Scholar
• Xiang, Feng, Yefa Hu, Yingrong Yu, and Huachun Wu. 2014. “QoS and Energy Consumption Aware Service Composition and Optimal-Selection Based on Pareto Group Leader Algorithm in Cloud Manufacturing System.” Central European Journal of Operations Research 22: 663–685.
   Web of Science ®Google Scholar
• Xiao, S., S. Sun, and J. J. Jin. 2017. “Surrogate Measures for the Robust Scheduling of Stochastic job Shop Scheduling Problems.” Energies 10 (4): 1–26. Article ID 543.
   Web of Science ®Google Scholar
• Xu, Bin, Jin Qi, Xiaoxuan Hu, Kwong-Sak Leung, Yanfei Sun, and Yu Xue. 2018. “Self-adaptive bat Algorithm for Large Scale Cloud Manufacturing Service Composition.” Peer-to-Peer Networking and Applications 11: 1115–1128.
   Web of Science ®Google Scholar
• Yang, Yefeng, Bo Yang, Shilong Wang, Tianguo Jin, and Shi Li. 2020. “An Enhanced Multi-Objective Grey Wolf Optimizer for Service Composition in Cloud Manufacturing.” Applied Soft Computing 87: 106003.
   Web of Science ®Google Scholar
• Yang, Yefeng, Bo Yang, Shilong Wang, Wei Liu, and Tianguo Jin. 2019a. “An Improved Grey Wolf Optimizer Algorithm for Energy-Aware Service Composition in Cloud Manufacturing.” International Journal of Advanced Manufacturing Technology 105: 3079–3091.
   Web of Science ®Google Scholar
• Yang, Yefeng, Bo Yang, Shilong Wang, Feng Liu, Yankai Wang, and Xiao Shu. 2019b. “A Dynamic ant-Colony Genetic Algorithm for Cloud Service Composition Optimization.” International Journal of Advanced Manufacturing Technology 102: 355–368.
   Web of Science ®Google Scholar
• Yongdong, Pan. 2018. “Bi-level Programming Optimization Method for Cloud Manufacturing Service Composition Based on Harmony Search.” Journal of Computational Science 27: 462–468.
   Web of Science ®Google Scholar
• Zeng, L. Z., B. Benatallah, A. H. H. Ngu, M. Dumas,J. Kalagnanam, and H. Chang. 2004. “QoS-aware Middleware for Web Services Composition.” IEEE Transactions on Software Engineering 30 (5): 311–327.
   Web of Science ®Google Scholar
• Zhang, Shuai, Song Xu, Xiaoling Huan, Wenyu Zhang, and Mingzhou Chen. 2019. “Networked Correlation-Aware Manufacturing Service Supply Chain Optimization Using an Extended Artificial bee Colony Algorithm.” Applied Soft Computing Journal 76: 121–139.
   Web of Science ®Google Scholar
• Zhang, Wenyu, Yushu Yang, Shuai Zhang, Dejian Yu, and Yong Chen. 2018. “A New Three-Dimensional Manufacturing Service Composition Method Under Various Structures Using Improved Flower Pollination Algorithm.” Enterprise Information Systems 12 (5): 620–637.
   Web of Science ®Google Scholar
• Zhao, Q. Y., L. Wei, and H. P. Shu. 2014. “Exception Handling Model of Manufacturing Equipment Cloud Service for Cloud Manufacturing Environment.” Journal of Graphics 35 (6): 840–846.
   Google Scholar
• Zheng, Hao, Yixiong Feng, and Jianrong Tan. 2016. “A Fuzzy QoS-Aware Resource Service Selection Considering Design Preference in Cloud Manufacturing System.” The International Journal of Advanced Manufacturing Technology 84: 371–379.
   Web of Science ®Google Scholar
• Zheng, Hao, Yixiong Feng, and Jianrong Tan. 2017. “A Hybrid Energy-Aware Resource Allocation Approach in Cloud Manufacturing Environment.” IEEE Access 5: 12648–12656.
   Web of Science ®Google Scholar
• Zhijie, Qi. 2004. “Discussions of Optimization Allocation Problem of Logistics Resources in China.” Modernization of Management 1: 45–46. (in Chinese).
   Google Scholar
• Zhou, J., and X. Yao. 2017a. “A Hybrid Approach Combining Modified Artificial bee Colony and Cuckoo Search Algorithms for Multi-Objective Cloud Manufacturing Service Composition.” International Journal of Production Research 55 (16): 4765–4784.
   Web of Science ®Google Scholar
• Zhou, J., and X. Yao. 2017b. “Multi-objective Hybrid Artificial bee Colony Algorithm Enhanced with Ĺevy Flight and Self-Adaption for Cloud Manufacturing Service Composition.” Applied Intelligence 47: 721–742.
   Web of Science ®Google Scholar
• Zhou, J., and X. Yao. 2017c. “Multi-population Parallel Self-Adaptive Differential Artificial bee Colony Algorithm with Application in Large-Scale Service Composition for Cloud Manufacturing.” Applied Soft Computing 56: 379–397.
   Web of Science ®Google Scholar
• Zhu, Li-Nan, Peng-Hang Li, and Xiao-Long Zhou. 2019. “IHDETBO: A Novel Optimization Method of Multi-Batch Subtasks Parallel-Hybrid Execution Cloud Service Composition for Cloud Manufacturing.” Complexity 2019: 1–21. Article ID 7438710.
   Google Scholar
• Zigao, Wu, Yu Shaohua, and Li Tiancheng. 2019. “A Meta-Model-Based Multi-Objective Evolutionary Approach to Robust Job Shop Scheduling.” Mathematics 7: 529.
   Web of Science ®Google Scholar