A novel hybrid algorithm for large-scale composition optimization problems in cloud manufacturing-Reference-Cited by-同舟云学术

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A novel hybrid algorithm for large-scale composition optimization problems in cloud manufacturing

Published:2021-07-02 Issue:9 Volume:34 Page:898-919
ISSN:0951-192X
Container-title:International Journal of Computer Integrated Manufacturing
language:en
Short-container-title:International Journal of Computer Integrated Manufacturing

Author:

Wang Zhongning¹,Wang Shilong¹,Yang Bo¹,Wang Yankai¹,Chen Ronghua¹

Affiliation:

1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China

Funder

Key Project of Technological Innovation and Application Development Plan of Chongqing

2030 Innovation Megaprojects of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2021.1946852

Reference43 articles.

1. Early prediction of quality of service using interface-level metrics, code-level metrics, and antipatterns

2. A TQCS-based service selection and scheduling strategy in cloud manufacturing

3. Study on machining service modes and resource selection strategies in cloud manufacturing

4. A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem

5. Tree Growth Algorithm (TGA): A novel approach for solving optimization problems

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1. Cloud Manufacturing Service Composition Optimization Based on Improved Chaos Sparrow Search Algorithm with Time-Varying Reliability and Credibility Evaluation;Symmetry;2024-06-19

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3. A technical perspective on integrating artificial intelligence to solid-state welding;The International Journal of Advanced Manufacturing Technology;2024-04-29

4. Knowledge-aware manufacturing services collaboration: A comprehensive study of evolutionary transfer optimization approaches;Advanced Engineering Informatics;2024-04

5. Collaborative optimization of manufacturing service allocation via multi-task transfer learning evolutionary approach;Journal of Intelligent Manufacturing;2024-03-01

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