An optimized MSW transfer station location system based on internet of things
Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station locatio...
Ausführliche Beschreibung
Autor*in: |
Chen, Yi [verfasserIn] Dai, Feng [verfasserIn] Cao, Mengjuan [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2021 |
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Anmerkung: |
© The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 |
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Übergeordnetes Werk: |
Enthalten in: International Journal of Systems Assurance Engineering and Management - Springer-Verlag, 2010, 12(2021), 4 vom: 08. Feb., Seite 675-688 |
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Übergeordnetes Werk: |
volume:12 ; year:2021 ; number:4 ; day:08 ; month:02 ; pages:675-688 |
Links: |
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DOI / URN: |
10.1007/s13198-021-01062-6 |
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SPR044520484 |
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10.1007/s13198-021-01062-6 doi (DE-627)SPR044520484 (SPR)s13198-021-01062-6-e DE-627 ger DE-627 rakwb eng Chen, Yi verfasserin aut An optimized MSW transfer station location system based on internet of things 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. Smart city (dpeaa)DE-He213 Waste transfer station location (dpeaa)DE-He213 NSGA-II (dpeaa)DE-He213 The ward clustering method (dpeaa)DE-He213 Dai, Feng verfasserin aut Cao, Mengjuan verfasserin aut Enthalten in International Journal of Systems Assurance Engineering and Management Springer-Verlag, 2010 12(2021), 4 vom: 08. Feb., Seite 675-688 (DE-627)SPR031222420 nnns volume:12 year:2021 number:4 day:08 month:02 pages:675-688 https://dx.doi.org/10.1007/s13198-021-01062-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 12 2021 4 08 02 675-688 |
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10.1007/s13198-021-01062-6 doi (DE-627)SPR044520484 (SPR)s13198-021-01062-6-e DE-627 ger DE-627 rakwb eng Chen, Yi verfasserin aut An optimized MSW transfer station location system based on internet of things 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. Smart city (dpeaa)DE-He213 Waste transfer station location (dpeaa)DE-He213 NSGA-II (dpeaa)DE-He213 The ward clustering method (dpeaa)DE-He213 Dai, Feng verfasserin aut Cao, Mengjuan verfasserin aut Enthalten in International Journal of Systems Assurance Engineering and Management Springer-Verlag, 2010 12(2021), 4 vom: 08. Feb., Seite 675-688 (DE-627)SPR031222420 nnns volume:12 year:2021 number:4 day:08 month:02 pages:675-688 https://dx.doi.org/10.1007/s13198-021-01062-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 12 2021 4 08 02 675-688 |
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10.1007/s13198-021-01062-6 doi (DE-627)SPR044520484 (SPR)s13198-021-01062-6-e DE-627 ger DE-627 rakwb eng Chen, Yi verfasserin aut An optimized MSW transfer station location system based on internet of things 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. Smart city (dpeaa)DE-He213 Waste transfer station location (dpeaa)DE-He213 NSGA-II (dpeaa)DE-He213 The ward clustering method (dpeaa)DE-He213 Dai, Feng verfasserin aut Cao, Mengjuan verfasserin aut Enthalten in International Journal of Systems Assurance Engineering and Management Springer-Verlag, 2010 12(2021), 4 vom: 08. Feb., Seite 675-688 (DE-627)SPR031222420 nnns volume:12 year:2021 number:4 day:08 month:02 pages:675-688 https://dx.doi.org/10.1007/s13198-021-01062-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 12 2021 4 08 02 675-688 |
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10.1007/s13198-021-01062-6 doi (DE-627)SPR044520484 (SPR)s13198-021-01062-6-e DE-627 ger DE-627 rakwb eng Chen, Yi verfasserin aut An optimized MSW transfer station location system based on internet of things 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. Smart city (dpeaa)DE-He213 Waste transfer station location (dpeaa)DE-He213 NSGA-II (dpeaa)DE-He213 The ward clustering method (dpeaa)DE-He213 Dai, Feng verfasserin aut Cao, Mengjuan verfasserin aut Enthalten in International Journal of Systems Assurance Engineering and Management Springer-Verlag, 2010 12(2021), 4 vom: 08. Feb., Seite 675-688 (DE-627)SPR031222420 nnns volume:12 year:2021 number:4 day:08 month:02 pages:675-688 https://dx.doi.org/10.1007/s13198-021-01062-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 12 2021 4 08 02 675-688 |
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10.1007/s13198-021-01062-6 doi (DE-627)SPR044520484 (SPR)s13198-021-01062-6-e DE-627 ger DE-627 rakwb eng Chen, Yi verfasserin aut An optimized MSW transfer station location system based on internet of things 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. Smart city (dpeaa)DE-He213 Waste transfer station location (dpeaa)DE-He213 NSGA-II (dpeaa)DE-He213 The ward clustering method (dpeaa)DE-He213 Dai, Feng verfasserin aut Cao, Mengjuan verfasserin aut Enthalten in International Journal of Systems Assurance Engineering and Management Springer-Verlag, 2010 12(2021), 4 vom: 08. Feb., Seite 675-688 (DE-627)SPR031222420 nnns volume:12 year:2021 number:4 day:08 month:02 pages:675-688 https://dx.doi.org/10.1007/s13198-021-01062-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 12 2021 4 08 02 675-688 |
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Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 |
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Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 |
abstract_unstemmed |
Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm. © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR044520484</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210710064912.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210710s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s13198-021-01062-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR044520484</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13198-021-01062-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chen, Yi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An optimized MSW transfer station location system based on internet of things</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Smart city</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Waste transfer station location</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">NSGA-II</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">The ward clustering method</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dai, Feng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cao, Mengjuan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">International Journal of Systems Assurance Engineering and Management</subfield><subfield code="d">Springer-Verlag, 2010</subfield><subfield code="g">12(2021), 4 vom: 08. 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