Cloud manufacturing service composition and optimal selection with sustainability considerations: a multi-objective integer bi-level multi-follower programming approach

The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and SCOS have generally focused on optimising the allocation of resources against quality of service (QoS), in terms of e.g. cost, quality, and ti...

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Published in:International journal of production research Vol. 58; no. 19; pp. 6024 - 6042
Main Authors: Wu, Yanxia, Jia, Guozhu, Cheng, Yang
Format: Journal Article
Language:English
Published: London Taylor & Francis 01.10.2020
Taylor & Francis LLC
Subjects:
Algorithms
cloud manufacturing
cloud service composition
Composition
Design optimization
Integers
Manufacturing
multi-objective integer bi-level multi-follower programming
Multiple objective analysis
particle swarm optimisation
quality of service
Social factors
Sustainability
sustainability of cloud manufacturing
ISSN:0020-7543, 1366-588X
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Abstract The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and SCOS have generally focused on optimising the allocation of resources against quality of service (QoS), in terms of e.g. cost, quality, and time. They have seldom taken the perspective of sustainability into discussion, although sustainability is indispensable in the CMfg environment. Addressing this gap, we aim to (1) propose a comprehensive method to assess the sustainability of cloud manufacturing (SoM) in terms of the economic, environmental, and social aspects; (2) establish a multi-objective integer bi-level multi-follower programming (MOIBMFP) model to simultaneously maximise SoM and QoS from the perspectives of both platform operator and multiple service demanders; and (3) design a hybrid particle swarm optimisation algorithm to solve the proposed MOIBMFP model. The experimental results show that the proposed algorithm is more feasible and effective than the typical multi-objective particle swarm optimisation algorithm when solving the proposed model. In other words, the proposed model and algorithm suggest better alternatives to meet the needs of the platform operator and service demanders in the CMfg environment.
AbstractList The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and SCOS have generally focused on optimising the allocation of resources against quality of service (QoS), in terms of e.g. cost, quality, and time. They have seldom taken the perspective of sustainability into discussion, although sustainability is indispensable in the CMfg environment. Addressing this gap, we aim to (1) propose a comprehensive method to assess the sustainability of cloud manufacturing (SoM) in terms of the economic, environmental, and social aspects; (2) establish a multi-objective integer bi-level multi-follower programming (MOIBMFP) model to simultaneously maximise SoM and QoS from the perspectives of both platform operator and multiple service demanders; and (3) design a hybrid particle swarm optimisation algorithm to solve the proposed MOIBMFP model. The experimental results show that the proposed algorithm is more feasible and effective than the typical multi-objective particle swarm optimisation algorithm when solving the proposed model. In other words, the proposed model and algorithm suggest better alternatives to meet the needs of the platform operator and service demanders in the CMfg environment.
Author Wu, Yanxia
Jia, Guozhu
Cheng, Yang
Author_xml – sequence: 1
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  fullname: Wu, Yanxia
  organization: School of Economics & Management, Beihang University
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  surname: Jia
  fullname: Jia, Guozhu
  organization: School of Economics & Management, Beihang University
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  givenname: Yang
  surname: Cheng
  fullname: Cheng, Yang
  email: cy@business.aau.dk
  organization: School of Business Administration, Jiangxi University of Finance and Economics
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Snippet The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and...
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SubjectTerms Algorithms
cloud manufacturing
cloud service composition
Composition
Design optimization
Integers
Manufacturing
multi-objective integer bi-level multi-follower programming
Multiple objective analysis
particle swarm optimisation
quality of service
Social factors
Sustainability
sustainability of cloud manufacturing
Title Cloud manufacturing service composition and optimal selection with sustainability considerations: a multi-objective integer bi-level multi-follower programming approach
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