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Resource scheduling in cloud-based manufacturing system: a comprehensive survey.
- Source :
- International Journal of Advanced Manufacturing Technology; Oct2022, Vol. 122 Issue 11/12, p4201-4219, 19p, 3 Color Photographs, 2 Diagrams, 3 Charts, 2 Graphs
- Publication Year :
- 2022
-
Abstract
- Inspired by cloud computing, cloud manufacturing (CMfg) is a service-oriented manufacturing paradigm on an on-demand and pay-as-you-go business model through the internet. More specifically, new challenges for production planning and decision-making process have emerged in that resource scheduling and have gained the most attention, and there is an urgent need to determine the current status and identify issues and matters to be addressed in the future. This review paper is aiming to discuss aspects of the cloud-based resource scheduling problem through investigating the literature to date to identify the existing gaps and recommending the potential paths moving forward for researchers in this field. So far, literature reviews focused on a broad scope of cloud-based scheduling, as a new approach taking a "narrow scope" by focusing on resource scheduling and various steps of it in the cloud environment are considered. Using the data gathered from the popular databases, a comprehensive statistical analysis on the existing literatures is provided, and the rational sequences of the systematic literature review (SLR) are elaborated. The mathematical models in resource scheduling are thoroughly elucidated. Then, a comprehensive analysis of the main aspects of resource scheduling including the objective functions, constraints, and optimization algorithms is presented. Discussion of the findings of the review paper illustrates that time and cost gain more attention (almost 80%) among all objective functions, and the metaheuristic algorithms are the most widely used in the recent research papers. Finally, suggestions for potential future research to further consolidate this field have been enumerated. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02683768
- Volume :
- 122
- Issue :
- 11/12
- Database :
- Complementary Index
- Journal :
- International Journal of Advanced Manufacturing Technology
- Publication Type :
- Academic Journal
- Accession number :
- 159500884
- Full Text :
- https://doi.org/10.1007/s00170-022-09873-y