A collaborative service group-based fuzzy QoS-aware manufacturing service composition using an extended flower pollination algorithm
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Quality of service (QoS)-aware manufacturing service composition has attracted growing attention from experts and scholars. However, most of them ignore the fuzziness and complexity of QoS values and describe QoS values using precise numbers. In addition, a one-to-one mapping-based service composition method has been widely used making it difficult to obtain an optimal solution with higher QoS values. In this study, we construct a new collaborative service group-based fuzzy QoS-aware (CSGFQ) manufacturing service composition model, which not only expands the traditional one-to-one mapping-based relationship between services and subtasks, but also objectively describes QoS values using fuzzy numbers. An extended flower pollination algorithm (FPA) that embeds four improvements is presented to solve the corresponding model. Four groups of experiments are performed to compare our proposed method with other baseline algorithms to prove the practicality, effectiveness, efficiency, and other performance of the extended FPA in solving the CSGFQ service composition problem.
KeywordsManufacturing service composition Collaborative service groups Fuzzy QoS-aware Extended flower pollination algorithm
This work was supported by the National Natural Science Foundation of China (Nos. 51475410, 51875503, 51775496) and Zhejiang Natural Science Foundation of China (No. LY17E050010).
Compliance with ethical standards
Conflict of interest
The authors declare that there is no conflict of interests regarding the publication of this article.
The authors state that this research complies with ethical standards. This research does not involve either human participants or animals.
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