Scheduling in cloud manufacturing: state-of-the-art and research challenges

Figures & data

Figure 1. Operation model of cloud manufacturing.

Figure 2. Procedure of scheduling in cloud manufacturing.

Table 1. Typical work on service composition in cloud manufacturing.

References	Algorithm	Nature of tasks	Performance criteria
Tao et al. (2013)	Chaos optimization	Single composite task	Time, cost, energy, reliability
Lartigau et al. (2015)	Artificial Bee Colony	Single sequentially executed task	Price, time, availability, reliability, maintainability, eco-impact
Jin, Yao, and Chen (2015)	Genetic algorithm	Single sequentially executed task	Time, cost, reliability, availability
Liu, Liu, and Sun (2013)	Genetic algorithm	Multiple homogeneous tasks	Time, cost, availability
Liu et al. (2013)	Genetic algorithm	Multiple heterogeneous tasks	Time, cost, availability
Liu and Zhang (2017)	Genetic algorithm	Single composite task	Time, cost, reliability
Zhou and Yao (2017d)	Teaching–learning-based optimization	Single composite task	Time, price, reliability, reputation
Zhou and Yao (2017c)	Artificial bee colony algorithm	Single composite task	Time, cost, availability, reliability
Zhou and Yao (2017a)	Artificial bee colony algorithm	Single composite task	Time, price, availability, reputation
Huang, Li, and Tao (2014)	Chaos optimization	Single composite task	Time, energy consumption, cost, reliability
Li et al. (2017)	Genetic algorithm	Multiple composite tasks	–
Chen et al. (2016)	Multi-objective evolutionary algorithm	Single composite task	Execution time, latency time, cost, reliability, availability
Xu and Sun (2016)	Bat algorithm	Single composite task	Time, availability, reliability
Zhou and Yao (2017b)	Bee colony algorithm	Single composite task	Time, price, availability, reputation, energy consumption
Xu et al. (2016)	Bees algorithm based on Pareto	Single composite task	Execution cost, response time
Liu, Ma, and Liu (2013)	Simulated annealing algorithm	Single hierarchical composite task	Time, cost, reliability, reputation
Xiang et al. (2016)	Pareto group leader algorithm	Single composite task	Service cost, service execution time span, service provider trust, service maintenance
Xiang et al. (2014)	Group leader algorithm	Single composite task	Time, cost, reliability
Zhang et al. (2016)	–	Single composite task	Cost, delivery time, delay time, reliability, credit, energy

Table 2. Typical work on scheduling in cloud manufacturing.

References	Scheduling algorithms	Performance criteria	Scheduling methods	Nature of tasks	Logistics
Laili, Zhang, and Tao (2011)	Genetic algorithm	Time	Static	Multiple sequentially executed design task	–
Li, Song, and Huang (2016)	Max percentages algorithm	Makespan, resource utilisation, load balancing	Static	single scientific workflow task	–
Lin and Chong (2017)	Genetic algorithm	Time	–	Single composite computing tasks	–
Li et al. (2012)	–	Cost, capability	Dynamic	Multiple composite tasks	✓
Tai et al. (2013)	Genetic ant colony algorithm	Time, capability, quality, cost	Dynamic	Multiple composite manufacturing tasks	✓
Cheng et al. (2014)	Genetic algorithm	Profit, task execution success rate	Static	Multiple composite, homogeneous manufacturing tasks	–
Jian and Wang (2014)	Particle swarm optimization	Time, cost	Static	Single composite manufacturing tasks	–
Ma et al. (2014)	Contract net	Time	Adaptive	Multiple tasks with different numbers of operations	–
Wang, Zhang, and Si (2014)	Particle swarm optimization	Time	Static	Multiple atomic manufacturing tasks	✓
Lartigau, Xu, and Zhan (2015)	Artificial bee colony	Availability, reliability	–	Single composite task	–
Mourtzis et al. (2015)	Intelligent search algorithm	Cost, time, quality	Adaptive	Multiple tasks	–
Cao et al. (2016)	Ant colony optimization	Time, cost, quality, service	Static	Single composite manufacturing task	✓
Li et al. (2017)	Genetic algorithm	Time, cost, load balancing	Static	Multiple composite, heterogeneous manufacturing tasks	✓
Jiang et al. (2016)	Genetic algorithm	Makespan, cost	Static	Multiple products to be disassembled	–
Li et al. (2016)	Specifically designed algorithms	Makespan	Static	Multiple homogeneous jobs	–
Liu et al. (2016), (2017)	Workload-based heuristic	Time, cost, quality	Static	Multiple heterogeneous manufacturing tasks	✓
Zhang et al. (2017)	Game theory	Time	Static	Multiple composite, heterogeneous manufacturing tasks	–
Lu et al. (2017)	Biogeography-based optimization	Time, load balancing, machine utilisation	Static	Multiple composite, heterogeneous manufacturing tasks	–
Xiao et al. (2015)	Shuffled frog leaping algorithm	Cost, time, capability utilisation, tardiness	Static	Manufacturing tasks	✓
Yuan et al. (2017)	Particle swarm optimization	Load balancing, reconstruction cost, delayed workload minimisation	Static	Multiple different kinds of products	–
Wang, Zhang, and Qi (2017)	Particle swarm optimization	Makespan	Static	Multiple jobs	–
Zhang et al. (2017)	Genetic algorithm	Cost, priority, reliability, energy consumption, customer satisfaction	Dynamic	Multiple independent orders	–
Zhou and Zhang (2016)	–	Time	Dynamic	Multiple composite tasks	✓
Zhou and Zhang (2016)	Event-triggered method	Time	Dynamic	Dynamically arriving composite tasks	✓

Figure 3. Number of articles published on different topics across different years (2010–2018).

Figure 4. Top ten journals publishing most papers on scheduling in cloud manufacturing (2010–2018).

Figure 5. Number of articles using different algorithms (or methods) from 2010 to 2018 on (a) service configuration, allocation and composition, and (b) service/task scheduling.

Tao, F. , Y. Laili , L. Xu , and L. Zhang . 2013. “FC-PACO-RM: A Parallel Method for Service Composition Optimal-Selection in Cloud Manufacturing System.” IEEE Transactions on Industrial Informatics 9 (4): 2023–2033.10.1109/TII.2012.2232936

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Lartigau, J. , X. Xu , L. Nie , and D. 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 (14): 4380–4404.10.1080/00207543.2015.1005765

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Jin, H. , X. Yao , and Y. Chen . 2015. “Correlation-aware QoS Modeling and Manufacturing Cloud Service Composition.” Journal of Intelligent Manufacturing 28 (8): 1947–1960. doi:10.1007/s10845-015-1080-2.

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Liu, W. N. , B. Liu , and D. H. Sun . 2013. “Multi-task Oriented Service Composition in Cloud Manufacturing.” [ In Chinese.] Computer Integrated Manufacturing Systems 19 (1): 199–209.

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Liu, W. , B. Liu , D. Sun , Y. Li , and G. 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): 786–805.10.1080/0951192X.2013.766939

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Liu, B. , and Z. Zhang . 2017. “QoS-aware Service Composition for Cloud Manufacturing Based on the Optimal Construction of Synergistic Elementary Service Groups.” International Journal of Advanced Manufacturing Technology 88 (9–12): 2757–2771.10.1007/s00170-016-8992-7

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Zhou, J. , and X. Yao . 2017d. “Hybrid Teaching–Learning-based Optimization of Correlation-aware Service Composition in Cloud Manufacturing.” International Journal of Advanced Manufacturing Technology . doi:10.1007/s00170-017-0008-8.

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Huang, B. , C. Li , and F. Tao . 2014. “A Chaos Control Optimal Algorithm for QoS-based Service Composition Selection in Cloud Manufacturing System.” Enterprise Information Systems 8 (4): 445–463.10.1080/17517575.2013.792396

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Xu, B. , and Z. Sun . 2016. “A Fuzzy Operator Based Bat Algorithm for Cloud Service Composition.” International Journal of Wireless and Mobile Computing 11 (1): 42–46.10.1504/IJWMC.2016.079471

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Xiang, F. , G. Z. Jiang , L. L. Xu , and N. X. Wang . 2016. “The Case-library Method for Service Composition and Optimal Selection of Big Manufacturing Data in Cloud Manufacturing System.” International Journal of Advanced Manufacturing Technology 84 (1–4): 59–70.10.1007/s00170-015-7813-8

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Xiang, F. , Y. Hu , Y. Yu , and H. 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 (4): 663–685.10.1007/s10100-013-0293-8

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Laili, Y. , L. Zhang , and F. Tao . 2011. “Energy Adaptive Immune Genetic Algorithm for Collaborative Design Task Scheduling in Cloud Manufacturing System.” Paper Presented at the IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, Singapore December 6–9.

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