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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Vydané v:	IEEE transactions on industrial informatics Ročník 15; číslo 6; s. 3712 - 3722
Hlavní autori:	Zhang, Yongping, Tao, Fei, Liu, Yang, Zhang, Pengyuan, Cheng, Ying, Zuo, Ying
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.06.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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Abstract	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.
AbstractList	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.
Author	Tao, Fei Zhang, Pengyuan Liu, Yang Cheng, Ying Zhang, Yongping Zuo, Ying
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SubjectTerms	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
Title	Long/Short-Term Utility Aware Optimal Selection of Manufacturing Service Composition Toward Industrial Internet Platforms
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