Long/Short-Term Utility Aware Optimal Selection of Manufacturing Service Composition Toward Industrial Internet Platforms

As numerous Industrial Internet platforms emerge, manufacturing services are shared among multiple stakeholders more frequently than ever before. The optimal selection of shared manufacturing service composition (MSC) should promise both the task completion and the stakeholders' satisfaction. H...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics Vol. 15; no. 6; pp. 3712 - 3722
Main Authors: Zhang, Yongping, Tao, Fei, Liu, Yang, Zhang, Pengyuan, Cheng, Ying, Zuo, Ying
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Classification
Composition
Genetic algorithms
Industrial Internet platform
Internet
long/short-term utility
Manufacturing
manufacturing service composition (MSC)
nondominated sorting genetic Algorithm-II (NSGA-II)
Optimization
Quality of service
Short term
Sorting algorithms
Stakeholders
Tabu search
Task analysis
Three-dimensional printing
Utilities
ISSN:1551-3203, 1941-0050
Online Access:Get full text
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Summary:As numerous Industrial Internet platforms emerge, manufacturing services are shared among multiple stakeholders more frequently than ever before. The optimal selection of shared manufacturing service composition (MSC) should promise both the task completion and the stakeholders' satisfaction. However, as commercial entities, stakeholders concentrate on not only the temporary benefits but also the long-term acquisitions. Most of the existing MSC problems neglect the stakeholders' prospect on the manufacturing service sharing. This leads to the disappointment and dissatisfaction of the stakeholders with long-term expectations, who will abandon the participation in Industrial Internet platforms. Therefore, the long/short-term preferences of various stakeholders should be satisfied and balanced. In this paper, the long/short-term utilities of three parties (provider, consumer, and operator) are first defined and discussed, and the models considering short-term utility of a consumer and long-term utility of providers are established. The potential tasks assigned to providers are taken into account to estimate the long-term utility if the current task is accepted. Then, to solve the biobjective optimization problem, an improved Nondominated Sorting Genetic Algorithm-II algorithm, combining Tabu search and improved K-means mechanism, is proposed to find the optimal solution set. Finally, the effectiveness of the method is verified by the experimental results in terms of solution diversity, astringency, and stability, in which a finding is further observed that the changes of consumers' preferences have little impact on the long-term utility of providers.
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2019.2892777