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TM-MOAOA: a two-stage task scheduling approach using TOPSIS and multi-objective Archimedes optimization in fog-cloud environment.

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Title: TM-MOAOA: a two-stage task scheduling approach using TOPSIS and multi-objective Archimedes optimization in fog-cloud environment.
Authors: Khaledian, Navid1, navid.khaledian@uni.lu, Razzaghzadeh, Shiva2, Shiva.razzaghzadeh@srbiau.ac.ir, Moazzami, Setareh3, s.moazzami@iautnb.ac.ir, Kivi, Parisa Norouzi2, parisa.norouzi.kivi@gmail.com
Source: Computing; Jul2025, Vol. 107 Issue 7, p1-31, 31p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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  Data: TM-MOAOA: a two-stage task scheduling approach using TOPSIS and multi-objective Archimedes optimization in fog-cloud environment.
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  Data: <searchLink fieldCode="AU" term="%22Khaledian%2C+Navid%22">Khaledian, Navid</searchLink><relatesTo>1</relatesTo>, <i>navid.khaledian@uni.lu</i><br /><searchLink fieldCode="AU" term="%22Razzaghzadeh%2C+Shiva%22">Razzaghzadeh, Shiva</searchLink><relatesTo>2</relatesTo>, <i>Shiva.razzaghzadeh@srbiau.ac.ir</i><br /><searchLink fieldCode="AU" term="%22Moazzami%2C+Setareh%22">Moazzami, Setareh</searchLink><relatesTo>3</relatesTo>, <i>s.moazzami@iautnb.ac.ir</i><br /><searchLink fieldCode="AU" term="%22Kivi%2C+Parisa+Norouzi%22">Kivi, Parisa Norouzi</searchLink><relatesTo>2</relatesTo>, <i>parisa.norouzi.kivi@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Computing%22">Computing</searchLink>; Jul2025, Vol. 107 Issue 7, p1-31, 31p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=186125938
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        Value: 10.1007/s00607-025-01513-z
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      – Code: eng
        Text: English
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        PageCount: 31
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      – TitleFull: TM-MOAOA: a two-stage task scheduling approach using TOPSIS and multi-objective Archimedes optimization in fog-cloud environment.
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            NameFull: Khaledian, Navid
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            NameFull: Razzaghzadeh, Shiva
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            NameFull: Moazzami, Setareh
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            – D: 01
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              Text: Jul2025
              Type: published
              Y: 2025
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              Value: 107
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