A hybrid teaching-learning-based optimization algorithm for QoS-aware manufacturing cloud service composition

Quality of service (QoS)-aware manufacturing cloud service composition (QoS-MCSC) is one of the key issues in Cloud manufacturing (CMfg). More and more manufacturing cloud services offering the same or similar functionality but different QoS attributes are provided in the CMfg platform. It is a chal...

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Published in:	Computing Vol. 104; no. 11; pp. 2489 - 2509
Main Authors:	Jin, Hong, Jiang, Cheng, Lv, Shengping, He, Haiping, Liao, Xinting
Format:	Journal Article
Language:	English
Published:	Vienna Springer Vienna 01.11.2022 Springer Nature B.V
Subjects:	Adaptive algorithms Artificial Intelligence Cloud computing Composition Computer Appl. in Administrative Data Processing Computer Communication Networks Computer Science Customer satisfaction Genetic algorithms Information Systems Applications (incl.Internet) Machine learning Manufacturing Mutation Optimization Quality of service Regular Paper Software Engineering Teaching Hybrid teaching-learning-based optimization 68T20 Quality of service 90-08 Cloud manufacturing Service composition 90C27
ISSN:	0010-485X, 1436-5057
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Abstract	Quality of service (QoS)-aware manufacturing cloud service composition (QoS-MCSC) is one of the key issues in Cloud manufacturing (CMfg). More and more manufacturing cloud services offering the same or similar functionality but different QoS attributes are provided in the CMfg platform. It is a challenging issue to construct an optimal composite service satisfying customers’ requirements. In this study, a novel hybrid teaching-learning-based optimization algorithm is proposed to solve QoS-MCSC problems. It integrates the advantages of uniform mutation, adaptive flower pollination algorithm, and teaching-learning-based optimization algorithm. The experimental results show that the proposed algorithm finds higher quality results than other compared algorithms.
AbstractList	Quality of service (QoS)-aware manufacturing cloud service composition (QoS-MCSC) is one of the key issues in Cloud manufacturing (CMfg). More and more manufacturing cloud services offering the same or similar functionality but different QoS attributes are provided in the CMfg platform. It is a challenging issue to construct an optimal composite service satisfying customers’ requirements. In this study, a novel hybrid teaching-learning-based optimization algorithm is proposed to solve QoS-MCSC problems. It integrates the advantages of uniform mutation, adaptive flower pollination algorithm, and teaching-learning-based optimization algorithm. The experimental results show that the proposed algorithm finds higher quality results than other compared algorithms.
Author	Jin, Hong Jiang, Cheng Lv, Shengping Liao, Xinting He, Haiping
Author_xml	– sequence: 1 givenname: Hong surname: Jin fullname: Jin, Hong organization: College of Engineering, South China Agricultural University – sequence: 2 givenname: Cheng surname: Jiang fullname: Jiang, Cheng organization: College of Engineering, South China Agricultural University – sequence: 3 givenname: Shengping surname: Lv fullname: Lv, Shengping email: lvshengping@scau.edu.cn organization: College of Engineering, South China Agricultural University – sequence: 4 givenname: Haiping surname: He fullname: He, Haiping organization: College of Engineering, South China Agricultural University – sequence: 5 givenname: Xinting surname: Liao fullname: Liao, Xinting organization: College of Engineering, South China Agricultural University
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Cites_doi	10.1016/j.ins.2019.05.065 10.1080/00207543.2017.1402137 10.1145/3389147 10.1016/j.future.2016.06.039 10.1016/j.eswa.2016.10.047 10.1016/j.cad.2010.12.015 10.1016/j.ins.2019.01.015 10.1177/0954405411405575 10.1007/s10845-015-1064-2 10.1016/j.future.2016.09.008 10.1016/j.rcim.2020.101991 10.1016/j.asoc.2019.106003 10.1016/j.rcim.2019.101832 10.1016/j.asoc.2017.04.029 10.1109/TSC.2015.2466572 10.1016/j.future.2020.05.006 10.1109/TSC.2015.2473840 10.1007/s10845-016-1215-0 10.1016/j.asoc.2015.11.012 10.1007/s00170-017-1167-3 10.1007/s10489-018-1301-4 10.1007/s10845-015-1080-2 10.1016/j.ejor.2009.02.025 10.1080/17517575.2013.792396 10.1080/00207543.2017.1292064 10.1007/s10489-017-1108-8 10.1016/j.future.2018.07.062 10.1016/j.ins.2011.08.006 10.1016/j.jvcir.2019.102687 10.1109/TEVC.2007.892759 10.1080/00207543.2018.1449978 10.1016/j.ins.2018.05.009 10.1007/s00500-020-04918-4 10.1007/978-3-642-32894-7_27 10.1007/978-3-642-17313-4_27 10.1145/1655925.1655991
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References	Zhang, Yang, Zhang, Yu, Li (CR9) 2018; 56 Seghir, Khababa (CR25) 2018; 29 Li, Zhang, Qin, He (CR15) 2020; 24 Liu, Wang, Wang, Xu, Zhang (CR6) 2019; 57 Chattopadhyay, Banerjee (CR30) 2020; 14 Zhang, Li (CR31) 2007; 11 Gavvala, Jatoth, Gangadharan, Buyya (CR26) 2019; 90 Mourad, Nassehi, Schaefer, Newman (CR2) 2020; 61 CR37 Tsai (CR13) 2019; 500 Cremene, Suciu, Pallez, Dumitrescu (CR4) 2016; 39 Zhou, Yao (CR36) 2017; 55 Rao, Savsani, Vakharia (CR11) 2012; 183 Zhang, Zhang, Liu, Hu (CR3) 2017; 28 Liu, Hu, Cai, Xing, Tan (CR35) 2019; 65 Rao, Savsani, Vakharia (CR10) 2011; 43 Ramírez, Parejo, Romero, Segura, Ruiz-Cortés (CR27) 2017; 72 Yang, Yang, Wang, Jin, Li (CR20) 2020; 87 Akbaripour, Houshmand, van Woensel, Mutlu (CR21) 2018; 95 Tao, Zhao, Hu, Zhou (CR7) 2010; 201 Yang, Yang, Wang, Jin, Li (CR33) 2020; 87 Khanouche, Attal, Amirat, Chibani, Kerkar (CR22) 2019; 482 CR29 CR28 Xu, Liu, Wang, Sheng, Yu, Wang (CR8) 2017; 68 Liang, Wen, Liu, Zhang, Zhang, Wang (CR34) 2021; 67 Tao, Zhang, Venkatesh, Luo, Cheng (CR1) 2011; 225 El Ghazi, Ahiod (CR12) 2018; 48 Ji, Ye, Zhou, Yin, Shen (CR16) 2017; 57 Jatoth, Gangadharan, Buyya (CR23) 2017; 10 Lu, Zhou, Zhu, Zhang, Liang, Xiao (CR18) 2020; 112 Kumar, Singh (CR14) 2019; 49 Zhou, Yao, Lin, Chan, Li (CR32) 2018; 456 Yu, Zhang (CR19) 2017; 68 Jin, Yao, Chen (CR5) 2017; 28 Huang, Li, Tao (CR24) 2014; 8 Sun, Zhao, Pan, Liu, Chen (CR17) 2018; 11 F Tao (1083_CR1) 2011; 225 Y Yang (1083_CR20) 2020; 87 M Cremene (1083_CR4) 2016; 39 C Jatoth (1083_CR23) 2017; 10 1083_CR37 L Yu (1083_CR19) 2017; 68 YF Yang (1083_CR33) 2020; 87 Z Li (1083_CR15) 2020; 24 BQ Huang (1083_CR24) 2014; 8 SK Gavvala (1083_CR26) 2019; 90 J Zhou (1083_CR36) 2017; 55 RV Rao (1083_CR11) 2012; 183 Y Zhang (1083_CR3) 2017; 28 HC Tsai (1083_CR13) 2019; 500 X Ji (1083_CR16) 2017; 57 H Jin (1083_CR5) 2017; 28 F Tao (1083_CR7) 2010; 201 H Akbaripour (1083_CR21) 2018; 95 Y Liu (1083_CR6) 2019; 57 Q Zhang (1083_CR31) 2007; 11 JW Liu (1083_CR35) 2019; 65 J Lu (1083_CR18) 2020; 112 J Zhou (1083_CR32) 2018; 456 A Ramírez (1083_CR27) 2017; 72 A El Ghazi (1083_CR12) 2018; 48 1083_CR28 X Xu (1083_CR8) 2017; 68 1083_CR29 F Seghir (1083_CR25) 2018; 29 MH Mourad (1083_CR2) 2020; 61 H Liang (1083_CR34) 2021; 67 ME Khanouche (1083_CR22) 2019; 482 Y Kumar (1083_CR14) 2019; 49 RV Rao (1083_CR10) 2011; 43 C Sun (1083_CR17) 2018; 11 S Chattopadhyay (1083_CR30) 2020; 14 W Zhang (1083_CR9) 2018; 56
References_xml	– volume: 500 start-page: 34 year: 2019 end-page: 47 ident: CR13 article-title: Confined teaching-learning-based optimization with variable search strategies for continuous optimization publication-title: Inf Sci doi: 10.1016/j.ins.2019.05.065 – volume: 56 start-page: 4676 issue: 14 year: 2018 end-page: 4691 ident: CR9 article-title: Correlation-aware manufacturing service composition model using an extended flower pollination algorithm publication-title: Int J Prod Res doi: 10.1080/00207543.2017.1402137 – volume: 14 start-page: 12 year: 2020 ident: CR30 article-title: QoS-aware automatic web service composition with multiple objectives publication-title: ACM Trans Web doi: 10.1145/3389147 – volume: 68 start-page: 128 year: 2017 end-page: 135 ident: CR19 article-title: Service composition based on multi-agent in the cooperative game publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2016.06.039 – volume: 72 start-page: 357 year: 2017 end-page: 370 ident: CR27 article-title: Evolutionary composition of QoS-aware web services: a many-objective perspective publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2016.10.047 – ident: CR37 – volume: 43 start-page: 303 issue: 3 year: 2011 end-page: 315 ident: CR10 article-title: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems publication-title: Comput Aided Des doi: 10.1016/j.cad.2010.12.015 – volume: 482 start-page: 419 year: 2019 end-page: 439 ident: CR22 article-title: Clustering-based and QoS-aware services composition algorithm for ambient intelligence publication-title: Inf Sci doi: 10.1016/j.ins.2019.01.015 – volume: 225 start-page: 1969 issue: 10 year: 2011 end-page: 1976 ident: CR1 article-title: Cloud manufacturing: a computing and service-oriented manufacturing model publication-title: Proc Inst Mech Eng Part B J Eng Manuf doi: 10.1177/0954405411405575 – volume: 28 start-page: 1109 year: 2017 end-page: 1123 ident: CR3 article-title: Research on services encapsulation and virtualization access model of machine for cloud manufacturing publication-title: J Intell Manuf doi: 10.1007/s10845-015-1064-2 – volume: 68 start-page: 304 year: 2017 end-page: 319 ident: CR8 article-title: S-ABC: a paradigm of service domain-oriented artificial bee colony algorithms for service selection and composition publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2016.09.008 – volume: 67 year: 2021 ident: CR34 article-title: Logistics-involved QoS-aware service composition in cloud manufacturing with deep reinforcement learning publication-title: Robot Comput Integr Manuf doi: 10.1016/j.rcim.2020.101991 – volume: 87 year: 2020 ident: CR33 article-title: An enhanced multi-objective grey wolf optimizer for service composition in cloud manufacturing publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.106003 – ident: CR29 – volume: 61 year: 2020 ident: CR2 article-title: Assessment of interoperability in cloud manufacturing publication-title: Robot Comput-Integr Manuf doi: 10.1016/j.rcim.2019.101832 – volume: 57 start-page: 504 year: 2017 end-page: 516 ident: CR16 article-title: An improved teaching-learning-based optimization algorithm and its application to a combinatorial optimization problem in foundry industry publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2017.04.029 – volume: 11 start-page: 616 issue: 4 year: 2018 end-page: 629 ident: CR17 article-title: Automated testing of WS-BPEL service compositions: a scenario-oriented approach publication-title: IEEE Trans Serv Comput doi: 10.1109/TSC.2015.2466572 – volume: 112 start-page: 330 year: 2020 end-page: 347 ident: CR18 article-title: DCEM: a data cell evolution model for service composition based on bigraph theory publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2020.05.006 – volume: 10 start-page: 475 issue: 3 year: 2017 end-page: 492 ident: CR23 article-title: Computational intelligence based QoS-aware web service composition: a systematic literature review publication-title: IEEE Trans Serv Comput doi: 10.1109/TSC.2015.2473840 – volume: 29 start-page: 1773 year: 2018 end-page: 1792 ident: CR25 article-title: A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition publication-title: J Intell Manuf doi: 10.1007/s10845-016-1215-0 – volume: 39 start-page: 124 year: 2016 end-page: 139 ident: CR4 article-title: Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2015.11.012 – volume: 95 start-page: 43 year: 2018 end-page: 70 ident: CR21 article-title: Cloud manufacturing service selection optimization and scheduling with transportation considerations: mixed-integer programming models publication-title: Int J Adv Manuf Tech doi: 10.1007/s00170-017-1167-3 – volume: 49 start-page: 1036 year: 2019 end-page: 1062 ident: CR14 article-title: A chaotic teaching learning based optimization algorithm for clustering problems publication-title: Appl Intell doi: 10.1007/s10489-018-1301-4 – volume: 87 year: 2020 ident: CR20 article-title: An enhanced multi-objective grey wolf optimizer for service composition in cloud manufacturing publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.106003 – volume: 28 start-page: 1947 issue: 8 year: 2017 end-page: 1960 ident: CR5 article-title: Correlation-aware QoS modeling and manufacturing cloud service composition publication-title: J Intell Manuf doi: 10.1007/s10845-015-1080-2 – volume: 201 start-page: 129 issue: 1 year: 2010 end-page: 143 ident: CR7 article-title: Correlation-aware resource service composition and optimal-selection in manufacturing grid publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2009.02.025 – volume: 8 start-page: 445 issue: 4 year: 2014 end-page: 463 ident: CR24 article-title: A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system publication-title: Enterp Inf Syst doi: 10.1080/17517575.2013.792396 – volume: 55 start-page: 4765 issue: 16 year: 2017 end-page: 4784 ident: CR36 article-title: A hybrid approach combining modified artificial bee colony and cuckoo search algorithms for multi-objective cloud manufacturing service composition publication-title: Int J Prod Res doi: 10.1080/00207543.2017.1292064 – volume: 48 start-page: 2755 year: 2018 end-page: 2769 ident: CR12 article-title: Energy efficient teaching-learning-based optimization for the discrete routing problem in wireless sensor networks publication-title: Appl Intell doi: 10.1007/s10489-017-1108-8 – volume: 90 start-page: 273 year: 2019 end-page: 290 ident: CR26 article-title: QoS-aware cloud service composition using eagle strategy publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2018.07.062 – ident: CR28 – volume: 183 start-page: 1 issue: 1 year: 2012 end-page: 15 ident: CR11 article-title: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems publication-title: Inf Sci doi: 10.1016/j.ins.2011.08.006 – volume: 65 year: 2019 ident: CR35 article-title: Large-scale and adaptive service composition based on deep reinforcement learning publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2019.102687 – volume: 11 start-page: 712 issue: 6 year: 2007 end-page: 731 ident: CR31 article-title: MOEA/D: a multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2007.892759 – volume: 57 start-page: 4854 issue: 15–16 year: 2019 end-page: 4879 ident: CR6 article-title: Scheduling in cloud manufacturing: state-of-the-art and research challenges publication-title: Int J Prod Res doi: 10.1080/00207543.2018.1449978 – volume: 456 start-page: 50 year: 2018 end-page: 82 ident: CR32 article-title: An adaptive multi-population differential artificial bee colony algorithm for many-objective service composition in cloud manufacturing publication-title: Inf Sci doi: 10.1016/j.ins.2018.05.009 – volume: 24 start-page: 15889 year: 2020 end-page: 15906 ident: CR15 article-title: A reformative teaching-learning-based optimization algorithm for solving numerical and engineering design optimization problems publication-title: Soft Comput doi: 10.1007/s00500-020-04918-4 – volume: 11 start-page: 616 issue: 4 year: 2018 ident: 1083_CR17 publication-title: IEEE Trans Serv Comput doi: 10.1109/TSC.2015.2466572 – volume: 72 start-page: 357 year: 2017 ident: 1083_CR27 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2016.10.047 – volume: 201 start-page: 129 issue: 1 year: 2010 ident: 1083_CR7 publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2009.02.025 – ident: 1083_CR37 doi: 10.1007/978-3-642-32894-7_27 – volume: 87 year: 2020 ident: 1083_CR20 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.106003 – volume: 57 start-page: 504 year: 2017 ident: 1083_CR16 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2017.04.029 – volume: 55 start-page: 4765 issue: 16 year: 2017 ident: 1083_CR36 publication-title: Int J Prod Res doi: 10.1080/00207543.2017.1292064 – volume: 48 start-page: 2755 year: 2018 ident: 1083_CR12 publication-title: Appl Intell doi: 10.1007/s10489-017-1108-8 – volume: 57 start-page: 4854 issue: 15–16 year: 2019 ident: 1083_CR6 publication-title: Int J Prod Res doi: 10.1080/00207543.2018.1449978 – volume: 225 start-page: 1969 issue: 10 year: 2011 ident: 1083_CR1 publication-title: Proc Inst Mech Eng Part B J Eng Manuf doi: 10.1177/0954405411405575 – volume: 65 year: 2019 ident: 1083_CR35 publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2019.102687 – volume: 68 start-page: 128 year: 2017 ident: 1083_CR19 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2016.06.039 – volume: 482 start-page: 419 year: 2019 ident: 1083_CR22 publication-title: Inf Sci doi: 10.1016/j.ins.2019.01.015 – volume: 500 start-page: 34 year: 2019 ident: 1083_CR13 publication-title: Inf Sci doi: 10.1016/j.ins.2019.05.065 – volume: 49 start-page: 1036 year: 2019 ident: 1083_CR14 publication-title: Appl Intell doi: 10.1007/s10489-018-1301-4 – volume: 24 start-page: 15889 year: 2020 ident: 1083_CR15 publication-title: Soft Comput doi: 10.1007/s00500-020-04918-4 – volume: 39 start-page: 124 year: 2016 ident: 1083_CR4 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2015.11.012 – volume: 68 start-page: 304 year: 2017 ident: 1083_CR8 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2016.09.008 – volume: 8 start-page: 445 issue: 4 year: 2014 ident: 1083_CR24 publication-title: Enterp Inf Syst doi: 10.1080/17517575.2013.792396 – volume: 95 start-page: 43 year: 2018 ident: 1083_CR21 publication-title: Int J Adv Manuf Tech doi: 10.1007/s00170-017-1167-3 – volume: 112 start-page: 330 year: 2020 ident: 1083_CR18 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2020.05.006 – volume: 10 start-page: 475 issue: 3 year: 2017 ident: 1083_CR23 publication-title: IEEE Trans Serv Comput doi: 10.1109/TSC.2015.2473840 – volume: 28 start-page: 1109 year: 2017 ident: 1083_CR3 publication-title: J Intell Manuf doi: 10.1007/s10845-015-1064-2 – volume: 183 start-page: 1 issue: 1 year: 2012 ident: 1083_CR11 publication-title: Inf Sci doi: 10.1016/j.ins.2011.08.006 – volume: 28 start-page: 1947 issue: 8 year: 2017 ident: 1083_CR5 publication-title: J Intell Manuf doi: 10.1007/s10845-015-1080-2 – volume: 456 start-page: 50 year: 2018 ident: 1083_CR32 publication-title: Inf Sci doi: 10.1016/j.ins.2018.05.009 – ident: 1083_CR28 doi: 10.1007/978-3-642-17313-4_27 – volume: 67 year: 2021 ident: 1083_CR34 publication-title: Robot Comput Integr Manuf doi: 10.1016/j.rcim.2020.101991 – volume: 90 start-page: 273 year: 2019 ident: 1083_CR26 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2018.07.062 – ident: 1083_CR29 doi: 10.1145/1655925.1655991 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 1083_CR31 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2007.892759 – volume: 61 year: 2020 ident: 1083_CR2 publication-title: Robot Comput-Integr Manuf doi: 10.1016/j.rcim.2019.101832 – volume: 14 start-page: 12 year: 2020 ident: 1083_CR30 publication-title: ACM Trans Web doi: 10.1145/3389147 – volume: 56 start-page: 4676 issue: 14 year: 2018 ident: 1083_CR9 publication-title: Int J Prod Res doi: 10.1080/00207543.2017.1402137 – volume: 43 start-page: 303 issue: 3 year: 2011 ident: 1083_CR10 publication-title: Comput Aided Des doi: 10.1016/j.cad.2010.12.015 – volume: 29 start-page: 1773 year: 2018 ident: 1083_CR25 publication-title: J Intell Manuf doi: 10.1007/s10845-016-1215-0 – volume: 87 year: 2020 ident: 1083_CR33 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.106003
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SubjectTerms	Adaptive algorithms Artificial Intelligence Cloud computing Composition Computer Appl. in Administrative Data Processing Computer Communication Networks Computer Science Customer satisfaction Genetic algorithms Information Systems Applications (incl.Internet) Machine learning Manufacturing Mutation Optimization Quality of service Regular Paper Software Engineering Teaching
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Title	A hybrid teaching-learning-based optimization algorithm for QoS-aware manufacturing cloud service composition
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