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A Multi-Service Composition Model for Tasks in Cloud Manufacturing Based on VS–ABC Algorithm

Author

Listed:
  • Di Liang

    (School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China)

  • Jieyi Wang

    (School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China)

  • Ran Bhamra

    (School of Business and Management Royal Holloway, University of London, Egham TW20 0EX, UK)

  • Liezhao Lu

    (School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China)

  • Yuting Li

    (School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China)

Abstract

This study analyzes the impact of Industry 4.0 and SARS-CoV-2 on the manufacturing industry, in which manufacturing entities are faced with insufficient resources and uncertain services; however, the current study does not fit this situation well. A multi-service composition for complex manufacturing tasks in a cloud manufacturing environment is proposed to improve the utilization of manufacturing service resources. Combining execution time, cost, energy consumption, service reliability and availability, a quality of service (QoS) model is constructed as the evaluation standard. A hybrid search algorithm (VS–ABC algorithm) based on the vortex search algorithm (VS) and the artificial bee colony algorithm (ABC) is introduced and combines the advantages of the two algorithms in search range and calculation speed. We take the customization production of automobiles as an example, and the case study shows that the VS–ABC algorithm has better applicability compared with traditional vortex search and artificial bee colony algorithms.

Suggested Citation

  • Di Liang & Jieyi Wang & Ran Bhamra & Liezhao Lu & Yuting Li, 2022. "A Multi-Service Composition Model for Tasks in Cloud Manufacturing Based on VS–ABC Algorithm," Mathematics, MDPI, vol. 10(21), pages 1-24, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:21:p:3968-:d:953104
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    References listed on IDEAS

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    Cited by:

    1. Mustafa Ibrahim Khaleel & Mejdl Safran & Sultan Alfarhood & Michelle Zhu, 2023. "A Hybrid Many-Objective Optimization Algorithm for Job Scheduling in Cloud Computing Based on Merge-and-Split Theory," Mathematics, MDPI, vol. 11(16), pages 1-28, August.

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