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Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform
Beihang Univ, Peoples R China.
Beihang Univ, Peoples R China.
Beihang Univ, Peoples R China.
Linköping University, Department of Management and Engineering, Environmental Technology and Management. Linköping University, Faculty of Science & Engineering. Univ Vaasa, Finland.ORCID iD: 0000-0001-8006-3236
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2019 (English)In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, Vol. 135, p. 1025-1035Article in journal (Refereed) Published
Abstract [en]

To realize collaboration among distributed enterprises, manufacturing service collaboration on Industrial Internet platform is an efficient method. However, the low degree of participation resulted by the sense of distrust, dissatisfaction, and insecurity hinders the widely application of Industrial Internet platform. Therefore, a secure, trustworthy, and multi-user satisfied manufacturing service collaboration method is in urgent need. A blockchain based platform could be utilized to support collaboration among distributed participants to complete trustworthy transactions. In addition, in order to satisfy multiple users, there should be a suitable collaboration mechanism that allows interest-independent participants to fulfil their short/long-term expectations and guide them to a consensus. Based on the establishment of the underlying data and network layer of the blockchain, the collaboration optimization of manufacturing services based on consensus is proposed. By utilizing Memetic algorithm, both the long-term utility of providers and the short-term utility of consumers are combined to choose the optimal providers for the tasks. The providers are selected with higher satisfaction degree of consumers.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD , 2019. Vol. 135, p. 1025-1035
Keywords [en]
Long/short-term utility; Manufacturing service collaboration; Blockchain; Industrial Internet platform; Memetic algorithm
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:liu:diva-160155DOI: 10.1016/j.cie.2019.05.039ISI: 000482244100076OAI: oai:DiVA.org:liu-160155DiVA, id: diva2:1349615
Note

Funding Agencies|National Natural Science Foundation of China (NSFC) [51875030]; National Key Research and Development Program of China [2016YFB1101700]; Beijing Science and Technology Project [Z181100003118001]

The accepted version of this article is available on the author's personal web page.

Available from: 2019-09-09 Created: 2019-09-09 Last updated: 2021-10-18

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