Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization
The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource sched...
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| Published in: | Journal of grid computing Vol. 21; no. 2; p. 24 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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01.06.2023
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| ISSN: | 1570-7873, 1572-9184, 1572-9184 |
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| Abstract | The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource scheduling system, because of the slow decision-making, it is difficult to meet the needs of the actual situation, especially in the face of emergencies, the traditional resource scheduling methods have great disadvantages. In order to solve the above problems, this paper takes emergency resource scheduling, a prominent scheduling problem, as an example. Based on Vague set theory and adaptive grid particle swarm optimization algorithm, a multi-objective emergency resource scheduling model is constructed under different conditions. This model can not only integrate the advantages of Vague set theory in dealing with uncertain problems, but also retain the advantages of adaptive grid particle swarm optimization that can solve multi-objective optimization problems and can quickly converge. The research results show that compared with the traditional resource scheduling optimization algorithm, the emergency resource scheduling model has higher resolution accuracy, more reasonable resource allocation, higher efficiency and faster speed in dealing with emergency events than the traditional resource scheduling model. Compared with the conventional fuzzy theory emergency resource scheduling model, its handling speed has increased by more than 3.82 times. |
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| AbstractList | The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource scheduling system, because of the slow decision-making, it is difficult to meet the needs of the actual situation, especially in the face of emergencies, the traditional resource scheduling methods have great disadvantages. In order to solve the above problems, this paper takes emergency resource scheduling, a prominent scheduling problem, as an example. Based on Vague set theory and adaptive grid particle swarm optimization algorithm, a multi-objective emergency resource scheduling model is constructed under different conditions. This model can not only integrate the advantages of Vague set theory in dealing with uncertain problems, but also retain the advantages of adaptive grid particle swarm optimization that can solve multi-objective optimization problems and can quickly converge. The research results show that compared with the traditional resource scheduling optimization algorithm, the emergency resource scheduling model has higher resolution accuracy, more reasonable resource allocation, higher efficiency and faster speed in dealing with emergency events than the traditional resource scheduling model. Compared with the conventional fuzzy theory emergency resource scheduling model, its handling speed has increased by more than 3.82 times. The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource scheduling system, because of the slow decision-making, it is difficult to meet the needs of the actual situation, especially in the face of emergencies, the traditional resource scheduling methods have great disadvantages. In order to solve the above problems, this paper takes emergency resource scheduling, a prominent scheduling problem, as an example. Based on Vague set theory and adaptive grid particle swarm optimization algorithm, a multi-objective emergency resource scheduling model is constructed under different conditions. This model can not only integrate the advantages of Vague set theory in dealing with uncertain problems, but also retain the advantages of adaptive grid particle swarm optimization that can solve multi-objective optimization problems and can quickly converge. The research results show that compared with the traditional resource scheduling optimization algorithm, the emergency resource scheduling model has higher resolution accuracy, more reasonable resource allocation, higher efficiency and faster speed in dealing with emergency events than the traditional resource scheduling model. Compared with the conventional fuzzy theory emergency resource scheduling model, its handling speed has increased by more than 3.82 times.The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource scheduling system, because of the slow decision-making, it is difficult to meet the needs of the actual situation, especially in the face of emergencies, the traditional resource scheduling methods have great disadvantages. In order to solve the above problems, this paper takes emergency resource scheduling, a prominent scheduling problem, as an example. Based on Vague set theory and adaptive grid particle swarm optimization algorithm, a multi-objective emergency resource scheduling model is constructed under different conditions. This model can not only integrate the advantages of Vague set theory in dealing with uncertain problems, but also retain the advantages of adaptive grid particle swarm optimization that can solve multi-objective optimization problems and can quickly converge. The research results show that compared with the traditional resource scheduling optimization algorithm, the emergency resource scheduling model has higher resolution accuracy, more reasonable resource allocation, higher efficiency and faster speed in dealing with emergency events than the traditional resource scheduling model. Compared with the conventional fuzzy theory emergency resource scheduling model, its handling speed has increased by more than 3.82 times. |
| ArticleNumber | 24 |
| Author | Yuan, Bo Zhang, Zheng Panneerselvam, John Han, Yibo Liu, Lu Han, Pu |
| Author_xml | – sequence: 1 givenname: Yibo surname: Han fullname: Han, Yibo organization: Nanyang Institute of Big Data Research, Nanyang Institute of Technology – sequence: 2 givenname: Pu surname: Han fullname: Han, Pu organization: School of Information Engineering, Nanyang Institute of Technology – sequence: 3 givenname: Bo surname: Yuan fullname: Yuan, Bo organization: Department of Informatics, University of Leicester – sequence: 4 givenname: Zheng surname: Zhang fullname: Zhang, Zheng email: zhangzheng@nyist.edu.cn organization: School of Computer and Software, Nanyang Institute of Technology – sequence: 5 givenname: Lu surname: Liu fullname: Liu, Lu organization: Department of Informatics, University of Leicester – sequence: 6 givenname: John surname: Panneerselvam fullname: Panneerselvam, John organization: Department of Informatics, University of Leicester |
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| Cites_doi | 10.1126/science.1087139 10.1109/ICLSIM.2010.5461242 10.1145/3321619.3321642 10.1016/j.tre.2016.12.011 10.1111/j.1467-7717.1984.tb00853.x 10.1109/ACCESS.2022.3175317 10.2112/JCR-SI107-097.1 10.1155/2021/9950198 10.1016/S0140-6736(03)13412-5 10.1080/02331934.2022.2048381 10.1016/j.iswa.2022.200157 10.1002/emp2.12034 10.1016/j.neucom.2017.09.086 10.1016/j.future.2017.11.031 10.1002/int.22183 10.1016/j.cor.2013.01.016 10.1016/j.knosys.2010.02.005 10.1016/j.jhin.2020.02.005 10.1061/41186(421)188 10.3390/ijgi6050142 10.1016/S0165-0114(98)00271-1 10.1109/TITS.2016.2515663 10.1016/j.procs.2018.03.043 10.1016/j.energy.2016.07.123 10.5055/jem.2020.0478 10.9746/jcmsi.10.77 10.1061/JHTRCQ.0000587 |
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| Keywords | Vague set theory Model Multi objective Resource scheduling Particle swarm optimization algorithm |
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| References | HM Wang (9660_CR14) 2018; 129 M Rostami (9660_CR33) 2022; 10 9660_CR28 9660_CR27 MS Kadhim (9660_CR30) 2022; 20 S Singh (9660_CR23) 2013; 2 9660_CR26 9660_CR6 N Perrier (9660_CR16) 2013; 40 X Huang (9660_CR17) 2020; 107 9660_CR24 9660_CR5 JS Peiris (9660_CR3) 2003; 361 F Heydarpoor (9660_CR10) 2020; 21 MJ Ebadi (9660_CR20) 2010; 23 K Renken (9660_CR7) 2020; 18 C Shang (9660_CR32) 2016; 114 K Guan (9660_CR1) 2016; 17 DH Hong (9660_CR35) 2000; 114 S Chang (9660_CR22) 2017; 10 9660_CR9 FY Yu (9660_CR25) 2017; 11 9660_CR19 CJ Jiang (9660_CR13) 2017; 6 9660_CR18 Y Zhou (9660_CR21) 2017; 99 D Kembull-cook (9660_CR8) 1984; 8 9660_CR15 R Wen (9660_CR29) 2013; 50 9660_CR36 9660_CR12 9660_CR34 9660_CR11 Y Guan (9660_CR2) 2003; 302 9660_CR31 J Yin (9660_CR4) 2010; 26 |
| References_xml | – ident: 9660_CR26 – volume: 302 start-page: 276 issue: 5643 year: 2003 ident: 9660_CR2 publication-title: Science doi: 10.1126/science.1087139 – ident: 9660_CR24 – volume: 50 start-page: 1464 issue: 7 year: 2013 ident: 9660_CR29 publication-title: J. Comput. Res. Dev. – volume: 20 start-page: 8143 issue: 6 year: 2022 ident: 9660_CR30 publication-title: NeuroQuantology – ident: 9660_CR31 doi: 10.1109/ICLSIM.2010.5461242 – ident: 9660_CR12 doi: 10.1145/3321619.3321642 – volume: 99 start-page: 77 year: 2017 ident: 9660_CR21 publication-title: Transp. Res. E Logist. Transp. Rev. doi: 10.1016/j.tre.2016.12.011 – ident: 9660_CR9 – volume: 8 start-page: 57 issue: 1 year: 1984 ident: 9660_CR8 publication-title: Disaster doi: 10.1111/j.1467-7717.1984.tb00853.x – volume: 10 start-page: 52508 year: 2022 ident: 9660_CR33 publication-title: IEEE Access doi: 10.1109/ACCESS.2022.3175317 – volume: 107 start-page: 437 issue: sp1 year: 2020 ident: 9660_CR17 publication-title: J. Coastal Res. doi: 10.2112/JCR-SI107-097.1 – ident: 9660_CR28 doi: 10.1155/2021/9950198 – volume: 361 start-page: 1767 issue: 9371 year: 2003 ident: 9660_CR3 publication-title: Lancet doi: 10.1016/S0140-6736(03)13412-5 – volume: 26 start-page: 30 issue: 2 year: 2010 ident: 9660_CR4 publication-title: Environ. Monit. China – ident: 9660_CR15 doi: 10.1080/02331934.2022.2048381 – ident: 9660_CR34 doi: 10.1016/j.iswa.2022.200157 – ident: 9660_CR6 doi: 10.1002/emp2.12034 – ident: 9660_CR18 doi: 10.1016/j.neucom.2017.09.086 – ident: 9660_CR27 doi: 10.1016/j.future.2017.11.031 – ident: 9660_CR36 doi: 10.1002/int.22183 – volume: 40 start-page: 1895 issue: 7 year: 2013 ident: 9660_CR16 publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2013.01.016 – volume: 23 start-page: 434 issue: 5 year: 2010 ident: 9660_CR20 publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2010.02.005 – ident: 9660_CR5 doi: 10.1016/j.jhin.2020.02.005 – ident: 9660_CR19 doi: 10.1061/41186(421)188 – volume: 6 start-page: 142 issue: 5 year: 2017 ident: 9660_CR13 publication-title: ISPRS Int. J. Geo-Inf. doi: 10.3390/ijgi6050142 – volume: 114 start-page: 103 issue: 1 year: 2000 ident: 9660_CR35 publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(98)00271-1 – volume: 17 start-page: 2171 issue: 8 year: 2016 ident: 9660_CR1 publication-title: IEEE Trans. Intell. Transp. Syst. doi: 10.1109/TITS.2016.2515663 – volume: 2 start-page: 225 issue: 6 year: 2013 ident: 9660_CR23 publication-title: Int. J. Adv. Res. Comput. Eng. Technol. – volume: 129 start-page: 208 year: 2018 ident: 9660_CR14 publication-title: Pro-cedia Comp. Sci. doi: 10.1016/j.procs.2018.03.043 – ident: 9660_CR11 – volume: 114 start-page: 671 year: 2016 ident: 9660_CR32 publication-title: Energy doi: 10.1016/j.energy.2016.07.123 – volume: 18 start-page: 341 issue: 4 year: 2020 ident: 9660_CR7 publication-title: J. Emerg. Manag. doi: 10.5055/jem.2020.0478 – volume: 10 start-page: 77 issue: 2 year: 2017 ident: 9660_CR22 publication-title: Sice J. Control Meas. Syst. Integr. doi: 10.9746/jcmsi.10.77 – volume: 21 start-page: 22 year: 2020 ident: 9660_CR10 publication-title: Algorithms – volume: 11 start-page: 100 issue: 3 year: 2017 ident: 9660_CR25 publication-title: J. Highway Transp. Res. Dev. (English Edition) doi: 10.1061/JHTRCQ.0000587 |
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| SubjectTerms | Algorithms Computer Science Decision making Emergencies Management of Computing and Information Systems Multiple objective analysis Optimization algorithms Particle swarm optimization Processor Architectures Resource allocation Resource scheduling Scheduling Set theory Traffic congestion Traffic jams User Interfaces and Human Computer Interaction |
| Subtitle | Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization |
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