A robust service composition and optimal selection method for cloud manufacturing-Reference-Cited by-同舟云学术

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A robust service composition and optimal selection method for cloud manufacturing

Published:2020-12-08 Issue: Volume: Page:1-19
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Yang Bo¹,Wang Shilong¹,Li Shi²,Jin Tianguo³

Affiliation:

1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, People’s Republic of China

2. Beijing Aerospace XinFeng Mechanical Equipment Co. Ltd., Beijing, People’s Republic of China

3. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, People’s Republic of China

Funder

the National Defense Basic Research Project of China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1852481

Reference58 articles.

1. Putting one-to-one marketing to work: Personalization, customization, and choice

2. A hybrid grey wolf optimizer algorithm with evolutionary operators for optimal QoS-aware service composition and optimal selection in cloud manufacturing

3. A flexible QoS-aware Web service composition method by multi-objective optimization in cloud manufacturing

4. A reinforcement learning based approach for multi-projects scheduling in cloud manufacturing

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2. A Quasi-Oppositional Learning-based Fox Optimizer for QoS-aware Web Service Composition in Mobile Edge Computing;Journal of Grid Computing;2024-08-31

3. An information freshness-based digital twin model to support multi-level complementary dynamic scheduling in Shared Manufacturing;Advanced Engineering Informatics;2024-08

4. An adaptive robust service composition and optimal selection method for cloud manufacturing based on the enhanced multi-objective artificial hummingbird algorithm;Expert Systems with Applications;2024-06

5. A two-phase method to optimize service composition in cloud manufacturing;Computing;2024-04-15

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